The impact of rising temperatures on the prevalence of coral diseases and their predictability: a global meta-analysis
This html documents the data calculation, cleaning, modeling, and visualization of a global meta-analysis of coral disease prevalence alongside rising ocean temperatures.
Data Wrangling and Calculation
Load Packages
library(tidyverse) # ggplot, dplyr, %>%, and friends
library(readxl) # read in excel files
library(visdat) # visualize missing data
library(maps) # map visualization
library(here) # read in data from project
library(rotl) # connect with the Open Tree of Life
library(ape) # for phylogenetic tree manipulation
library(RDS) # save RDS files
library(BiocManager) # install and manage Bioconductor packages
library(ggtree) # devtools::install_github("YuLab-SMU/ggtree")
library(ggtreeExtra) # devtools::install_github("xiangpin/ggtreeExtra")
library(ggnewscale) # add colour layers in phylogenetic trees
library(R.utils) # programming utilities
library(ncdf4) # read ncdf files
library(lubridate) # working with dates and times
library(RCurl) # HTTP interface
library(birk) # data summaries
library(lme4) # linear mixed models
library(rstan) # Stan models
library(glmmTMB) # run small GLMMs quickly
library(modelr) # pipelines
library(brms) # bayesian modeling through Stan
library(tidybayes) # manipulate Stan objects in a tidy way
library(broom) # convert model objects to data frames
library(broom.mixed) # convert brms model objects to data frames
library(emmeans) # calculate marginal effects in even fancier ways
library(patchwork) # combine ggplot objects
library(ggokabeito) # neat accessible color palette
library(gghalves) # special half geoms
library(ggbeeswarm) # special distribution-shaped point jittering
library(ggdist) # distribution visualisation
library(igraph) # manually alter plots
library(ggpubr) # manually alter plots
library(ggExtra) # additional plot tools
library(kableExtra) # for tablesLoad Data
Data was originally organized in an excel file where each sheet of the excel file contained different data with a common identifier between all (Effect Size ID and Paper ID).
Effect Size Data sheet contained information relevant to the effect size calculation (as believed to be relevant at start of project).
Bibliographic Data sheet contained details of the bibliographic information to identify paper and effect size IDs to proper publication.
Transect Data sheet contained information relevant to sample collection (i.e., survey method and dimensions).
Moderator Data sheet contained additional information not directly related to effect size calculation (e.g., Total Sample Area size, number of corals - if provided, etc.).
Disease Data sheet contained all the diseases identified in studies and recorded how many disease incorporated in each disease prevalence metric and which diseases are present (“1”) or absent (“0”) in that sample.
Species Data sheet contained information relevant to the species included in each study. Since most studies do not separate the disease prevalence metric by species, this data sheet was only linked to the others by Paper ID.
# Check that file isn't open in excel
# Read in each excel sheet
prevESD <- read_excel(path = here("data", "Coral Disease Extracted Data.xlsx"), sheet = "Effect Size Data")
bibdata <- read_excel(path = here("data", "Coral Disease Extracted Data.xlsx"), sheet = "Bibliographic Data")
prevTRAN <- read_excel(path = here("data", "Coral Disease Extracted Data.xlsx"), sheet = "Transect Data")
prevMOD <- read_excel(path = here("data", "Coral Disease Extracted Data.xlsx"), sheet = "Moderator Data")
prevDIS <- read_excel(path = here("data", "Coral Disease Extracted Data.xlsx"), sheet = "Disease Data")
prevSPP <- read_excel(path = here("data", "Coral Disease Extracted Data.xlsx"), sheet = "Real Species Data")
# List of included studies
papers <- subset(bibdata, Paper_ID!="")Organize Data
# visualize missing data
dat.list <- list(prevDIS, prevESD, prevMOD, prevSPP, prevTRAN)
missing<- lapply(dat.list, vis_miss)
missing# Remove data with no effect sizes
ESD <- subset(prevESD, Effect_ID!="")
MOD <- subset(prevMOD, Effect_ID!="")
TRAN <- subset(prevTRAN, Effect_ID!="")
DIS <- subset(prevDIS, Effect_ID!="")# Only keep effect sizes measured as disease prevalence in %
percentonly <- subset(prevESD, Unit_Prevalence!="col/100m^2" &
Unit_Prevalence!="col/m^2" &
Unit_Prevalence!="mean no. colonies/m^2" &
Unit_Prevalence!="no. col" &
Effect_ID!="")
# Visualize missing data patterns
vis_miss(percentonly)# The regions extracted from papers were too precise. Therefore, we redefined regions based on ocean basins
ocean_group <- function(Region_HoeghGuldberg) {
case_when(
Region_HoeghGuldberg == "Western Indian Ocean" | Region_HoeghGuldberg=="Eastern Indian Ocean" ~ "Indian Ocean",
Region_HoeghGuldberg=="Western Pacific" | Region_HoeghGuldberg=="Coral Triangle & SE Asia" ~ "Pacific Ocean",
Region_HoeghGuldberg=="Caribbean & Gulf of Mexico" | Region_HoeghGuldberg=="XXXX" ~ "Atlantic Ocean"
)
}
# Create a new column for oceans
percentonly$Ocean <- ocean_group(percentonly$Region_HoeghGuldberg)Extract Sea Surface Temperature (SST) Data
As most studies didn’t provide the temperature data at the sample site, we needed to calculate this data using an external dataset. We used NOAA COBE2 available at NOAA Physical Sciences Laboratory website
Load in SST data
# Get data from NOAA database
url = "ftp://ftp.cdc.noaa.gov/Datasets/COBE2/sst.mon.mean.nc"
bin = getBinaryURL(url)
writeBin(bin, "mon.sst.nc")
SSTData <- nc_open(filename = "mon.sst.nc")
rm(bin)
file.remove("mon.sst.nc")
# Set variables from dataset
lon <- ncvar_get(SSTData, varid = "lon")
lat <- ncvar_get(SSTData, varid = "lat")
time <- ncvar_get(SSTData, varid = "time")
sst <- ncvar_get(SSTData, varid = "sst")
# Set time as a date to match extracted data
dim(sst)
SSTData$dim$time$units
sst.date <- as.Date("1891-01-01") + timeCreate functions
Needed to extract SST, time, and location
# First define a helper function that extracts middle value (or average of 2 middle values) from a vector).
midval <- function(x) {
if(length(x)%%2 == 1) {
return(x[ceiling(length(x)/2)])
} else return(mean(c(x[length(x)/2], x[length(x)/2 + 1]), na.rm = T))
}
# Define a function for extracting mean SST value at a particular location from a particular time period
sst_extract <- function(start_date, end_date, data_source,
lon_index, lat_index,
summer = F,
fun = mean, ...) {
require("lubridate")
if(summer) {
if(lat_index <= 90) {
month(start_date) <- 6
end_date <- start_date
month(end_date) <- 8
} else if(lat_index > 90) {
month(start_date) <- 12
end_date <- start_date
month(end_date) <- 2
year(end_date) <- year(end_date) + 1
}
}
start_date_units <- as.numeric(start_date - as.Date("1891-01-01"))
end_date_units <- as.numeric(end_date - as.Date("1891-01-01"))
start_date_index <- which(time == start_date_units)
end_date_index <- which(time == end_date_units)
# ...and extract data
sst_extract <- data_source[lon_index, lat_index, seq(start_date_index, end_date_index)]
# Here we assign data for i-th record to our list...
return(fun(sst_extract, ...))
}
# Create function which finds the closest coordinate in SST dataset from our extracted dataset
find_close <- function(datasource, lon_ix, lat_ix, step = 3, summer = F, start_date, end_date, diagn = F) {
lon_steps = seq(lon_ix - step, lon_ix + step)
lat_steps = seq(lat_ix - step, lat_ix + step)
longitudes = numeric(length(lon_steps)) + 1
latitudes = numeric(length(lat_steps)) + 1
names(longitudes) = lon_steps
names(latitudes) = lat_steps
for(i in 1:length(longitudes)) {
sst_vals = sst_extract(start_date = start_date, end_date = end_date, data_source = datasource,
lat_index = lat_ix,
lon_index = as.numeric(names(longitudes)[i]),
summer = summer,
fun = function(x) return(x))
longitudes[i] = any(!is.na(sst_vals))
}
for(i in 1:length(latitudes)) {
sst_vals = sst_extract(start_date = start_date, end_date = end_date, data_source = datasource,
lon_index = lon_ix,
lat_index = as.numeric(names(latitudes)[i]),
summer = summer,
fun = function(x) return(x))
latitudes[i] = any(!is.na(sst_vals))
}
if (diagn) {
return(rbind(longitudes, latitudes))
} else {
if(any(longitudes == 1)) {
for (k in 1:step) {
if (longitudes[step + 1 + k] == 1) {
lon_new = as.numeric(names(longitudes)[step + 1 + k])
break
} else if (longitudes[step + 1 - k] == 1) {
lon_new = as.numeric(names(longitudes)[step + 1 - k])
break
}
}
lon_ix = lon_new
} else {
for (k in 1:step) {
if (latitudes[step + 1 + k] == 1) {
lat_new = as.numeric(names(latitudes)[step + 1 + k])
break
} else if (latitudes[step + 1 - k] == 1) {
lat_new = as.numeric(names(latitudes)[step + 1 - k])
break
}
}
lat_ix = lat_new
}
return(c(lon_ix, lat_ix))
}
}
# Create a function to identify survey season from sampling period
season_extract <- function(start_date, end_date, lat_index) {
require('lubridate')
N_seasons <- c(rep('win', 2), rep('spr', 3), rep('sum', 3), rep('aut', 3), 'win')
S_seasons <- c(rep('sum', 2), rep('aut', 3), rep('win', 3), rep('spr', 3), 'sum')
if (as.numeric(difftime(end_date, start_date)) < 100) {
if (lat_index <= 90) {
return(names(sort(table(N_seasons[month(start_date):month(end_date)]), decreasing = T))[1])
} else if (lat_index > 90) {
return(names(sort(table(S_seasons[month(start_date):month(end_date)]), decreasing = T))[1])
}
} else return('multi')
}
# Assign month names to number values
months <- c(Jan = "01", Feb = "02", Mar = "03",
Apr = "04", May = "05", Jun = "06",
Jul = "07", Aug = "08", Sep = "09",
Oct = "10", Nov = "11", Dec = "12")
# Set extracted data as dataframe
percentonly <- as.data.frame(percentonly)
# Create columns for values to go into in dataframe
percentonly$average_SST <- NA
percentonly$middle_SST <- NA
percentonly$sd_SST <- NA
percentonly$start_month <- NA
percentonly$end_month <- NA
percentonly$average_SST_summer <- NA
percentonly$middle_SST_summer <- NA
percentonly$sd_SST_summer <- NA
# Allow coordinates to round to the nearest 0.5 degree to best match to SST dataset
coord_grid <- function(coord) floor(coord) + 0.5Calculate SST
# Rename in case any variables accidentally get changed, so original is saved
percentonly_ <- percentonly
for (i in 1:nrow(percentonly_)) {
# cat(i); cat("\n")
if (grepl("^[A-Z]{1}[a-z]{2}$",
percentonly_[i, "Month"])) {
# this condition looks for cases with one month
start.month <- end.month <- percentonly_[i, "Month"]
start.yr <- end.yr <- percentonly_[i, "Year"]
} else if (grepl("^([A-Z]{1}[a-z]{2}), (?:[A-Z]{1}[a-z]{2}, )*([A-Z]{1}[a-z]{2})$",
percentonly_[i, "Month"])) {
# this condition looks for lists of month separated by ", "
start.month <- gsub("^([A-Z]{1}[a-z]{2}), (?:[A-Z]{1}[a-z]{2}, )*([A-Z]{1}[a-z]{2})$",
replacement = "\\1",
percentonly_[i, "Month"])
end.month <- gsub("^([A-Z]{1}[a-z]{2}), (?:[A-Z]{1}[a-z]{2}, )*([A-Z]{1}[a-z]{2})$",
replacement = "\\2",
percentonly_[i, "Month"])
start.yr <- percentonly_[i, "Year"]
end.yr <- ifelse(which(names(months) == end.month) > which(names(months) == start.month),
start.yr, start.yr + 1)
} else if (grepl("^([A-Z]{1}[a-z]{2})-[A-Z]{1}[a-z]{2}, (?:[A-Z]{1}[a-z]{2}-[A-Z]{1}[a-z]{2}, )*[A-Z]{1}[a-z]{2}-([A-Z]{1}[a-z]{2})$",
percentonly_[i, "Month"])) {
# this condition looks for ranges of months signified by "-" in multiple ranges
start.month <- gsub("^([A-Z]{1}[a-z]{2})-[A-Z]{1}[a-z]{2}, (?:[A-Z]{1}[a-z]{2}-[A-Z]{1}[a-z]{2}, )*[A-Z]{1}[a-z]{2}-([A-Z]{1}[a-z]{2})$",
replacement = "\\1",
percentonly_[i, "Month"])
end.month <- gsub("^([A-Z]{1}[a-z]{2})-[A-Z]{1}[a-z]{2}, (?:[A-Z]{1}[a-z]{2}-[A-Z]{1}[a-z]{2}, )*[A-Z]{1}[a-z]{2}-([A-Z]{1}[a-z]{2})$",
replacement = "\\2",
percentonly_[i, "Month"])
start.yr <- percentonly_[i, "Year"]
end.yr <- ifelse(which(names(months) == end.month) > which(names(months) == start.month),
start.yr, start.yr + 1)
} else if (grepl("^([A-Z]{1}[a-z]{2})-([A-Z]{1}[a-z]{2})$",
percentonly_[i, "Month"])) {
# this condition looks for ranges of months signified by "-"
start.month <- gsub("^([A-Z]{1}[a-z]{2})-([A-Z]{1}[a-z]{2})$",
replacement = "\\1",
percentonly_[i, "Month"])
end.month <- gsub("^([A-Z]{1}[a-z]{2})-([A-Z]{1}[a-z]{2})$",
replacement = "\\2",
percentonly_[i, "Month"])
start.yr <- percentonly_[i, "Year"]
end.yr <- ifelse(which(names(months) == end.month) > which(names(months) == start.month),
start.yr, start.yr + 1)
} else if (percentonly_[i, "Month"] == 0) {
start.yr <- end.yr <- percentonly_[i, "Year"]
if(percentonly_[i, "Lat"] > 0) start.month <- end.month <- "Jul"
if(percentonly_[i, "Lat"] < 0) start.month <- end.month <- "Jan"
} else start.month <- end.month <- middle.month <- -999
if (start.month!= -999) {
lat_index <- which(lat == coord_grid(percentonly_[i, "Lat"])) # ...extract relevant indexes...
lon_index <- which(lon == coord_grid(ifelse(percentonly_[i, "Lon"] < 0,
360 + percentonly_[i, "Lon"],
percentonly_[i, "Lon"])))
start_date <- as.Date(paste(start.yr, "-", months[start.month], "-01", sep = ""))
end_date <- as.Date(paste(end.yr, "-", months[end.month], "-01", sep = ""))
if(any(is.na(sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = F, function(x) return (x))))) {
lon_index = find_close(datasource = sst, lon_ix = lon_index, lat_ix = lat_index,
step = 10, summer = F, start_date = start_date, end_date = end_date)[1]
lat_index = find_close(datasource = sst, lon_ix = lon_index, lat_ix = lat_index,
step = 10, summer = F, start_date = start_date, end_date = end_date)[2]
}
percentonly_[i, "start_month"] <- as.numeric(format(start_date, "%m"))
percentonly_[i, "end_month"] <- as.numeric(format(end_date, "%m"))
percentonly_[i, "average_SST"] <- sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = F, mean, na.rm = T)
percentonly_[i, "middle_SST"] <- sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = F, midval)
percentonly_[i, "sd_SST"] <- sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = F, sd, na.rm = T)
percentonly_[i, "average_SST_summer"] <- sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = T, mean, na.rm = T)
percentonly_[i, "middle_SST_summer"] <- sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = T, midval)
percentonly_[i, "sd_SST_summer"] <- sst_extract(start_date, end_date, sst,
lon_index, lat_index, summer = T, sd, na.rm = T)
percentonly_[i, "season"] <- season_extract(start_date, end_date, lat_index)
} else if (start.month == -999) {
} else stop("Error in month formatting\n")
}
# rename back to original once finished
percentonly <- percentonly_
## Check sst data coverage
out <- array(0, dim = c(360, 180, 2040))
plot(1:360, 1:360, type = "n", ylim = c(1,180))
for (i in 1:360) {
for (j in 1:180) {
for(k in 1:2040) {
if(!is.na(sst[i,j,k])) {
# points(lon[i], lat[j])
out[i,j,k] <- out[i,j,k] + 1
}
}
}
}
out1 <- rowSums(out, dims = 2)
dim(out1)
plot(1:360, 1:360, type = "n", ylim = c(180,1))
for (i in 1:360) {
for(j in 1:180) {
points(i, j, cex = 0.001 * out1[i,j])
}
}# Check if averages make sense with middle month values
ggplot(percentonly, aes(x = average_SST, y = middle_SST)) + geom_point()
# remove NaN results
TStemp <- subset(percentonly, (middle_SST == "NaN"))Check values
# Check correlation between year and average SST
cor.test(percentonly$Year, percentonly$average_SST)
ggplot(percentonly, mapping = aes(Year, average_SST, col = abs(Lat))) +
geom_jitter() +
geom_smooth()
# Check by lat values without <25
ggplot(percentonly, mapping = aes(Year, middle_SST, col = abs(Lat))) +
geom_jitter() +
geom_smooth()
ggplot(percentonly, mapping = aes(Year, average_SST, col = abs(Lat))) +
geom_point() +
geom_smooth(method = "lm")
ggplot(percentonly, mapping = aes(Year, average_SST_summer, col = abs(Lat))) +
geom_point() +
geom_smooth(method = "lm")Combine Data Sheets
# Combine into one dataset
percentonly %>% left_join(MOD, by = c("Effect_ID", "Paper_ID")) %>%
left_join(TRAN, by = c("Effect_ID", "Paper_ID")) %>%
left_join(DIS, by = c("Effect_ID", "Paper_ID")) -> dat_with_70s
rdsdat <- dat_with_70sNew SST Database for WSSTA
We needed to utilize a finer resolution database to calculate Weekly Sea Surface Temperature Anomaly (WSSTA), so we chose the daily SST database available through Copernicus which spans from January 1981 to present. This can be accessed at Copernicus Data
We downloaded all between July 1988 and June 2018, unzipped all files into one shared “sst” folder. This folder is separate from the R Project as the R Project was kept in a shared drive and this folder was too big to upload and move (166GB). The files are organized in this folder with the names given by the Copernicus download, which begins with the YearMonthDay of the recorded SST values (e.g., 20180630…).
Load data
Calculation for WSSTA
### load folder with daily sst files
nc_sst_day <- nc_open("D:/Sam's Lenovo/Documents/sst/19880702120000-ESACCI-L4_GHRSST-SSTdepth-OSTIA-GLOB_CDR2.0-v02.0-fv01.0.nc")
#### creation of new NC files with weekly averages ----
# first define dimensions
lonvar <- ncvar_get(nc_sst_day, "lon")
latvar <- ncvar_get(nc_sst_day, "lat")
londim <- ncdim_def("longitude", "degrees_east", lonvar)
latdim <- ncdim_def("latitude", "degrees_north", latvar)
timedim <- ncdim_def("time", "seconds from 1981-1-1", 1, unlim = T)
# now define variables
sstvar <- ncvar_def("sst", "kelvin", dim = list(londim, latdim, timedim), prec = "float")
# create file
sstdata <- nc_create("sst_1988_2018.nc", list(sstvar))
# list individual day files
myfiles <- list.files("D:/Sam's Lenovo/Documents/sst")
# loop over files and fill new NC file
i <- 1 # day counter
j <- 1 # weeks counter
for (current_file in myfiles) {
# open the given sst data in the loop
nc_temp <- nc_open(paste("D:/Sam's Lenovo/Documents/sst/", current_file, sep = ''))
sst_temp <- ncvar_get(nc_temp, 'analysed_sst')
if(i == 1) {
time_temp <- ncvar_get(nc_temp, 'time')
sst_avg <- (1/7)*sst_temp
} else {
sst_avg <- sst_avg + (1/7)*sst_temp
}
rm(sst_temp)
nc_close(nc_temp)
if (i == 7) {
# open file to write
sstdata <- nc_open("sst_1988_2018.nc", write = T)
# write data
ncvar_put(sstdata, "sst", sst_avg, start = c(1, 1, j), count = c(-1, -1, 1))
# update the time variable with the new day
ncvar_put(sstdata, "time", time_temp, start = j, count = 1)
# close connection before the next iteration and cleanup data
nc_close(sstdata)
rm(sst_avg)
i <- 1
j <- j + 1
} else {
i <- i + 1
}
cat("File "); cat(current_file); cat(" done \n")
}
#### extract and add monthly averages maxima ----
mmm <- nc_open(here("data",'ct5km_climatology_v3.1.nc'))
lons <- round(ncvar_get(mmm, 'lon'), 3)
lats <- round(ncvar_get(mmm, 'lat'), 3)
rdsdat$MMM <- NA
# loop over data to fill MMM climatology values
for (i in 1:nrow(rdsdat)) {
if(rdsdat[i, "Year"] > 1989) {
# rounding strategy to get correct rounding resolution
lon_index <- which(lons == round(floor(rdsdat[i,'Lon']/0.05)*0.05 + 0.025, 3))
lat_index <- which(lats == round(floor(rdsdat[i,'Lat']/0.05)*0.05 + 0.025, 3))
# adding 273.15 turns Celsius into Kelvin
mmm_val <- ncvar_get(mmm, 'sst_clim_mmm',
start = c(lon_index, lat_index, 1),
count = c(1,1,1)) + 273.15
rdsdat[i, 'MMM'] <- mmm_val
}
cat('Entry '); cat(i); cat(' done\n')
}
nc_close(mmm)
#### extract WSSTA weekly ----
sst <- nc_open('sst_1988_2018.nc')
lons <- round(ncvar_get(sst, 'longitude'), 3)
lats <- round(ncvar_get(sst, 'latitude'), 3)
time <- ncvar_get(sst, 'time')
rdsdat$WSSTA <- NA
for (i in 1:nrow(rdsdat)){
if (any(is.na(rdsdat[i, "start_month"]))) {
next
}
if(rdsdat[i, 'Year'] <= 1989) {
next
}
sample.date <- as.Date(paste(rdsdat[i,"Year"], "-",
rdsdat[i,"start_month"], "-", "01", sep = ""))
start.date <- as.numeric(sample.date - as.Date('1981-1-1'))*24*3600
start.week <- time[which.closest(time, start.date)]
end.week <- time[which.closest(time, (as.numeric(sample.date - as.Date('1981-1-1'))-365)*24*3600)]
timewindow <- subset(time, end.week <= time & time <= start.week)
end.week <- which(time == end.week)
# Get all weekly values from SSTData for given coordinates and input into vector
lon_index <- which(lons == round(floor(rdsdat[i,'Lon']/0.05)*0.05 + 0.025, 3))
lat_index <- which(lats == round(floor(rdsdat[i,'Lat']/0.05)*0.05 + 0.025, 3))
# Extract variables
year.sst <- ncvar_get(sst, varid = "sst", start = c(lon_index,lat_index,end.week), count = c(1,1,length(timewindow)))
# cat(year.sst); cat("\n")
# Check if for every set of coordinates, there is a corresponding temperature
if (all(is.nan(year.sst) == TRUE)) {
cat('Entry '); cat(i); cat('needs coordinate adjustments') # Row number that needs coordinate checking for if land
next
}
threshold <- rdsdat[i, 'MMM']
# Calculate WSSTA with comparison to threshold
heatweek <- c()
for (k in 1:length(year.sst)) { # k is an index for a position in year.sst
hotspot.dev <- year.sst[k] - threshold
if (is.nan(hotspot.dev) == TRUE | is.na(hotspot.dev) == TRUE){
print("NA")
}
if (hotspot.dev > 1) {
heatweek <- c(heatweek, hotspot.dev)
} else {
next # distinguish between those that were not higher than threshold vs those that were NA or NaN
}
}
rdsdat[i, "WSSTA"] <- sum(heatweek)
cat('Entry '); cat(i); cat(' done\n')
}
nc_close(sst)Remove Missing Data
# Remove pre-1992 data since WSSTA climatology is from 1985-1992 and don't want to compare values to themselves
dat_post92 <- subset(rdsdat, WSSTA != "Inf")
# Remove NAs
dat_WSSTA <- subset(dat_post92, WSSTA != "")
dat_Area <- subset(dat_WSSTA, Sample_Area_km2 != "")
dat_Tran <- subset(dat_Area, Transect_Type != "")
dat_DisNum <- subset(dat_Tran, Disease_Num != "")
# Rename data to something simpler
rdsdat <- dat_DisNumComplete Dataset
rdsdat <- readRDS(here("data", "CompletedData.rds"))
kable(rdsdat) %>% kable_styling("striped", position="left") %>%
scroll_box(width = "100%", height = "300px")| ï..Effect_ID | Paper_ID | Site_ID | Disease_Prevalence | Unit_Prevalence | DiseasePrev_SE | SourcePrev | Year | Month_Old | Month | SourceYear | Location | SourceLocation | Region_HoeghGuldberg | Region_Kleypas | Lat_Old | Lon_Old | Lat | Lon | SourceLatLon | SST_C | SourceTemp | Notes.x | Ocean | average_SST | middle_SST | sd_SST | start_month | end_month | average_SST_summer | middle_SST_summer | sd_SST_summer | season | month.Lat | season.Lat | DiseasePrev_SD | SST_SE | SST_SD | Sample_Area_km2 | Site_Num | SourceSite_Num | Coral_N | Mixed_Sp | Notes.y | Transect_Type | Transect_Num | Transect_Length_m | Transect_Width_m | Plot_area_m.2 | SourceTransect | Notes.x.x | Disease_Num | WS | BBD | GA | BrB | SEB | UWS | TL | DSS | WB | YBD | WPx | IMS | Trema | Cyano | PS | AN | PR | PUWS | DWS | RBD | STGA | RM | RW | PLS | PWPS | CT | PBTL | WPa | Cilia | PBSS | GPD | Unknown | Notes.y.y | DHW | MMM | WSSTA | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | EI0001 | CD001 | SI001 | 0.7200000 | % | NA | Results p220 | 1992 | Jul | Jul | Results p220 | Key Largo National Marine Sanctuary | Materials and Methods p220 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123611 | -80.29694 | 25.123611 | -80.29694 | Figure 1 Dry Rocks reef, GoogleMaps | NA | NA | 10 corals infected | Atlantic Ocean | 28.98000 | 28.9800 | NA | 7 | 7 | 28.67100 | 28.980 | 0.8449923 | sum | 7 | summer | NA | NA | NA | 9.42400 | 30 | Results p220 | 1397 | 1 | NA | Belt | 1 | 62.8320 | 2.00 | 125.6640 | Materials and Methods p220 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6960526 | 302.72 | 0.000000 |
| 2 | EI0002 | CD001 | SI001 | 0.1400000 | % | NA | Results p220 | 1992 | Nov | Nov | Results p220 | Key Largo National Marine Sanctuary | Materials and Methods p220 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123611 | -80.29694 | 25.123611 | -80.29694 | Figure 1 Dry Rocks reef, GoogleMaps | NA | NA | 2 corals infected | Atlantic Ocean | 26.46300 | 26.4630 | NA | 11 | 11 | 28.67100 | 28.980 | 0.8449923 | aut | 11 | fall | NA | NA | NA | 9.42400 | 30 | Results p220 | 1397 | 1 | NA | Belt | 1 | 62.8320 | 2.00 | 125.6640 | Materials and Methods p220 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7489243 | 302.72 | 0.000000 |
| 3 | EI0003 | CD001 | SI001 | 0.3600000 | % | NA | Results p220 | 1993 | Jul | Jul | Results p220 | Key Largo National Marine Sanctuary | Materials and Methods p220 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123611 | -80.29694 | 25.123611 | -80.29694 | Figure 1 Dry Rocks reef, GoogleMaps | NA | NA | 5 corals infected | Atlantic Ocean | 29.18300 | 29.1830 | NA | 7 | 7 | 28.78600 | 29.183 | 1.1500923 | sum | 7 | summer | NA | NA | NA | 9.42400 | 30 | Results p220 | 1397 | 1 | NA | Belt | 1 | 62.8320 | 2.00 | 125.6640 | Materials and Methods p220 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4360657 | 302.72 | 0.000000 |
| 4 | EI0004 | CD002 | SI002 | 2.9000000 | % | NA | Table 2 | 2015 | 0 | 0 | Methods 2015 two-year post-grounding surveys | Tubbataha Reefs Natural Park | Introduction | Coral Triangle & SE Asia | Southeast Asia | 8.806097 | 119.81659 | 8.806097 | 119.81659 | GoogleMaps TRNP South Atoll, Figure 1 | NA | NA | USSG Ground Zero | Pacific Ocean | 29.20000 | 29.2000 | NA | 7 | 7 | 29.62267 | 29.200 | 0.4632946 | sum | 7 | summer | 7.9000000 | NA | NA | 0.38000 | 9 | Methods 2015 two-year post-grounding surveys | 285 | 1 | Coral_N USSG Ground Zero and Impact Border combined | Belt | 9 | 10.0000 | 1.00 | 10.0000 | Methods 2015 two-year post-grounding surveys | USSG Ground Zero | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2596283 | 302.69 | 4.318552 |
| 5 | EI0005 | CD002 | SI002 | 13.5000000 | % | NA | Table 2 | 2015 | 0 | 0 | Methods 2015 two-year post-grounding surveys | Tubbataha Reefs Natural Park | Introduction | Coral Triangle & SE Asia | Southeast Asia | 8.806097 | 119.81659 | 8.806097 | 119.81659 | GoogleMaps TRNP South Atoll, Figure 1 | NA | NA | USSG Impact Border | Pacific Ocean | 29.20000 | 29.2000 | NA | 7 | 7 | 29.62267 | 29.200 | 0.4632946 | sum | 7 | summer | 5.4000000 | NA | NA | 0.38000 | 9 | Methods 2015 two-year post-grounding surveys | 285 | 1 | Coral_N USSG Ground Zero and Impact Border combined | Belt | 7 | 10.0000 | 1.00 | 10.0000 | Methods 2015 two-year post-grounding surveys | USSG Impact Border east: n=4, west: n=3 | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2596283 | 302.69 | 4.318552 |
| 6 | EI0006 | CD002 | SI003 | 1.6000000 | % | NA | Table 2 | 2015 | 0 | 0 | Methods 2015 two-year post-grounding surveys | Tubbataha Reefs Natural Park | Introduction | Coral Triangle & SE Asia | Southeast Asia | 8.750452 | 119.82706 | 8.750452 | 119.82706 | GoogleMaps TRNP South Atoll, Figure 1 | NA | NA | USSG Control (3-S) | Pacific Ocean | 29.20000 | 29.2000 | NA | 7 | 7 | 29.62267 | 29.200 | 0.4632946 | sum | 7 | summer | 2.7000000 | NA | NA | 0.38000 | 9 | Methods 2015 two-year post-grounding surveys | 529 | 1 | USSG Control (3-S) | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Methods 2015 two-year post-grounding surveys | USSG Control (3-S) | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1853714 | 302.68 | 4.252849 |
| 7 | EI0007 | CD002 | SI004 | 8.9000000 | % | NA | Table 2 | 2015 | 0 | 0 | Methods 2015 two-year post-grounding surveys | Tubbataha Reefs Natural Park | Introduction | Coral Triangle & SE Asia | Southeast Asia | 8.849522 | 119.91465 | 8.849522 | 119.91465 | GoogleMaps TRNP Ranger Station, Figure 1 | NA | NA | MPY Ground Zero | Pacific Ocean | 29.20000 | 29.2000 | NA | 7 | 7 | 29.62267 | 29.200 | 0.4632946 | sum | 7 | summer | 10.2000000 | NA | NA | 0.38000 | 9 | Methods 2015 two-year post-grounding surveys | 274 | 1 | Coral_N MPY Ground Zero and Impact Border combined | Belt | 3 | 10.0000 | 1.00 | 10.0000 | Methods 2015 two-year post-grounding surveys | MPY Ground Zero | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2643051 | 302.68 | 4.358562 |
| 8 | EI0008 | CD002 | SI004 | 10.4000000 | % | NA | Table 2 | 2015 | 0 | 0 | Methods 2015 two-year post-grounding surveys | Tubbataha Reefs Natural Park | Introduction | Coral Triangle & SE Asia | Southeast Asia | 8.849522 | 119.91465 | 8.849522 | 119.91465 | GoogleMaps TRNP Ranger Station, Figure 1 | NA | NA | MPY Impact Border | Pacific Ocean | 29.20000 | 29.2000 | NA | 7 | 7 | 29.62267 | 29.200 | 0.4632946 | sum | 7 | summer | 9.9000000 | NA | NA | 0.38000 | 9 | Methods 2015 two-year post-grounding surveys | 274 | 1 | Coral_N MPY Ground Zero and Impact Border combined | Belt | 9 | 10.0000 | 1.00 | 10.0000 | Methods 2015 two-year post-grounding surveys | MPY Impact Border lagoonal: n=3, seaweed near: n=3, seaweed far: n=3 | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2643051 | 302.68 | 4.358562 |
| 9 | EI0009 | CD002 | SI004 | 2.4000000 | % | NA | Table 2 | 2015 | 0 | 0 | Methods 2015 two-year post-grounding surveys | Tubbataha Reefs Natural Park | Introduction | Coral Triangle & SE Asia | Southeast Asia | 8.849522 | 119.91465 | 8.849522 | 119.91465 | GoogleMaps TRNP Ranger Station, Figure 1 | NA | NA | MPY Control (1-N) | Pacific Ocean | 29.20000 | 29.2000 | NA | 7 | 7 | 29.62267 | 29.200 | 0.4632946 | sum | 7 | summer | 0.1000000 | NA | NA | 0.38000 | 9 | Methods 2015 two-year post-grounding surveys | 1339 | 1 | MPY Control (1-N) | Belt | 2 | 20.0000 | 1.00 | 20.0000 | Methods 2015 two-year post-grounding surveys | MPY Control (1-N) | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2643051 | 302.68 | 4.358562 |
| 10 | EI0010 | CD003 | SI005 | 0.9028777 | % | 0.794964 | Figure 4, MPA | 2013 | Aug-Sep | Aug-Sep | Methods 2.1 p58 | Koh Tau | Methods 2.1 p58 | Coral Triangle & SE Asia | Southeast Asia | 10.092280 | 99.83849 | 10.092280 | 99.83849 | GoogleMaps Koh Tao, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio | Pacific Ocean | 28.53750 | 28.5375 | 0.0601048 | 8 | 9 | 29.07933 | 29.200 | 0.5343187 | aut | 8 | summer | 1.3769181 | NA | NA | 0.54000 | 3 | Results 3.3.1 p60 | 6373 | 1 | NA | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Methods 2.1 p58 | NA | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Unusual (non-focal) bleaching patterns referred to as Unknown White Syndrome | 0.4443054 | 303.30 | 0.000000 |
| 11 | EI0011 | CD003 | SI005 | 0.5287770 | % | 0.3561151 | Figure 4, non-MPA | 2013 | Aug-Sep | Aug-Sep | Methods 2.1 p58 | Koh Tau | Methods 2.1 p58 | Coral Triangle & SE Asia | Southeast Asia | 10.092280 | 99.83849 | 10.092280 | 99.83849 | GoogleMaps Koh Tao, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio | Pacific Ocean | 28.53750 | 28.5375 | 0.0601048 | 8 | 9 | 29.07933 | 29.200 | 0.5343187 | aut | 8 | summer | 0.6168095 | NA | NA | 0.54000 | 3 | Results 3.3.1 p60 | 6373 | 1 | NA | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Methods 2.1 p58 | NA | 6 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Unusual (non-focal) bleaching patterns referred to as Unknown White Syndrome | 0.4443054 | 303.30 | 0.000000 |
| 12 | EI0012 | CD004 | SI006 | 4.5000000 | % | 1.2 | Results p4 | 2011 | Dec | Dec | Methods in situ surveys of belt transects | Montebello and Barrow Islands, NW Australia | Methods in situ surveys of belt transects | Eastern Indian Ocean | Australia | -20.595150 | 115.49348 | -20.595150 | 115.49348 | GoogleMaps Montebello and Barrow Islands | NA | NA | NA | Indian Ocean | 27.63000 | 27.6300 | NA | 12 | 12 | 28.62200 | 28.938 | 0.8777522 | sum | 6 | summer | NA | NA | NA | 0.52500 | 12 | Figure 1 | 5498 | 1 | NA | Belt | 3 | 15.0000 | 1.00 | 15.0000 | Methods in situ surveys of belt transects | one site had 10m transects | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3735657 | 302.07 | 0.000000 |
| 13 | EI0013 | CD006 | SI007 | 0.1650000 | % | 0.05 | Results Spatial and temporal occurrence of disease Coral diseases p457 | 2010 | Jan | Jan | Materials and Methods Disease surveys p456 | Grande Terre, New Caledonia | Figure 1 | Western Pacific | Melanesia | -21.432377 | 165.45553 | -21.459280 | 165.12087 | GoogleMaps Grande Terre, Figure 1 | NA | NA | NA | Pacific Ocean | 26.64000 | 26.6400 | NA | 1 | 1 | 27.15633 | 27.548 | 0.7576666 | sum | 7 | summer | NA | NA | NA | 3.78000 | 13 | Table 1 | 47166 | 1 | NA | Belt | 2 | 25.0000 | 1.00 | 25.0000 | Materials and Methods Disease Surveys p456 | NA | 11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | disease reported as genus-specific, but here grouped based on visual symptom | 1.5699768 | 300.27 | 5.188527 |
| 14 | EI0014 | CD006 | SI007 | 0.2870000 | % | 0.1 | Results Spatial and temporal occurrence of disease Coral diseases p457 | 2013 | Feb | Feb | Materials and Methods Disease surveys p456 | Grande Terre, New Caledonia | Figure 1 | Western Pacific | Melanesia | -21.432377 | 165.45553 | -21.459280 | 165.12087 | GoogleMaps Grande Terre, Figure 1 | NA | NA | NA | Pacific Ocean | 27.40800 | 27.4080 | NA | 2 | 2 | 26.83100 | 27.048 | 0.5318114 | sum | 8 | summer | NA | NA | NA | 3.60000 | 12 | Table 1 | 38251 | 1 | NA | Belt | 2 | 25.0000 | 1.00 | 25.0000 | Materials and Methods Disease Surveys p456 | NA | 9 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | disease reported as genus-specific, but here grouped based on visual symptom | 1.0121460 | 300.27 | 4.537109 |
| 15 | EI0015 | CD008 | SI008 | 4.9000000 | % | NA | Table 2A | 1998 | Aug | Aug | Table 1A | Andros Island, Bahamas | Methods p78 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.355060 | -77.66884 | 24.355060 | -77.66884 | Averaged from Table 1A | NA | NA | Reef-crest sites | Atlantic Ocean | 30.02500 | 30.0250 | NA | 8 | 8 | 29.48933 | 29.753 | 0.7054766 | sum | 8 | summer | 3.2000000 | NA | NA | 0.70000 | 7 | Table 2 | 744 | 1 | NA | Line | 10 | 10.0000 | 1.00 | 10.0000 | Methods p79, Table 2 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8371277 | 302.26 | 0.000000 |
| 17 | EI0017 | CD007 | SI010 | 0.0021000 | % | NA | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8021622 | 301.60 | 15.488447 |
| 18 | EI0018 | CD007 | SI010 | 0.0007128 | % | NA | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8021622 | 301.60 | 15.488447 |
| 19 | EI0019 | CD007 | SI010 | 0.0000000 | % | 0 | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8021622 | 301.60 | 15.488447 |
| 20 | EI0020 | CD007 | SI010 | 0.0014000 | % | NA | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8021622 | 301.60 | 15.488447 |
| 21 | EI0021 | CD007 | SI010 | 0.0043000 | % | NA | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8021622 | 301.60 | 15.488447 |
| 22 | EI0022 | CD007 | SI010 | 0.0000000 | % | 0 | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8021622 | 301.60 | 15.488447 |
| 23 | EI0023 | CD007 | SI010 | 0.0007128 | % | NA | Table 1 calculated using sample size in Results p4 | 2005 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.75000 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14400 | 29.1440 | 0.4115367 | 10 | 11 | 29.18767 | 29.065 | 0.2910778 | aut | 10 | fall | NA | NA | NA | 1.29000 | 16 | Results p4 | 1403 | 1 | NA | Line | 129 | 10.0000 | 1.00 | 10.0000 | Results p4, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | NA | 0.8021622 | 301.60 | 15.488447 |
| 24 | EI0024 | CD007 | SI010 | 0.0028000 | % | NA | Table 1 calculated using sample size in Results p5 | 2006 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.12500 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14000 | 29.1400 | 0.2899137 | 10 | 11 | 28.67600 | 28.525 | 0.2093630 | aut | 10 | fall | NA | NA | NA | 1.32000 | 16 | Results p3 | 1416 | 1 | NA | Line | 132 | 10.0000 | 1.00 | 10.0000 | Results p3, Methods p3 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5164490 | 301.60 | 9.275682 |
| 25 | EI0025 | CD007 | SI010 | 0.0007062 | % | NA | Table 1 calculated using sample size in Results p5 | 2006 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.12500 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14000 | 29.1400 | 0.2899137 | 10 | 11 | 28.67600 | 28.525 | 0.2093630 | aut | 10 | fall | NA | NA | NA | 1.32000 | 16 | Results p3 | 1416 | 1 | NA | Line | 132 | 10.0000 | 1.00 | 10.0000 | Results p3, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5164490 | 301.60 | 9.275682 |
| 26 | EI0026 | CD007 | SI010 | 0.0042000 | % | NA | Table 1 calculated using sample size in Results p5 | 2006 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.12500 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14000 | 29.1400 | 0.2899137 | 10 | 11 | 28.67600 | 28.525 | 0.2093630 | aut | 10 | fall | NA | NA | NA | 1.32000 | 16 | Results p3 | 1416 | 1 | NA | Line | 132 | 10.0000 | 1.00 | 10.0000 | Results p3, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5164490 | 301.60 | 9.275682 |
| 27 | EI0027 | CD007 | SI010 | 0.0106000 | % | NA | Table 1 calculated using sample size in Results p5 | 2006 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.12500 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14000 | 29.1400 | 0.2899137 | 10 | 11 | 28.67600 | 28.525 | 0.2093630 | aut | 10 | fall | NA | NA | NA | 1.32000 | 16 | Results p3 | 1416 | 1 | NA | Line | 132 | 10.0000 | 1.00 | 10.0000 | Results p3, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5164490 | 301.60 | 9.275682 |
| 28 | EI0028 | CD007 | SI010 | 0.0141000 | % | NA | Table 1 calculated using sample size in Results p5 | 2006 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.12500 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14000 | 29.1400 | 0.2899137 | 10 | 11 | 28.67600 | 28.525 | 0.2093630 | aut | 10 | fall | NA | NA | NA | 1.32000 | 16 | Results p3 | 1416 | 1 | NA | Line | 132 | 10.0000 | 1.00 | 10.0000 | Results p3, Methods p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5164490 | 301.60 | 9.275682 |
| 29 | EI0029 | CD007 | SI010 | 0.0014000 | % | NA | Table 1 calculated using sample size in Results p5 | 2006 | Oct-Nov | Oct-Nov | Materials and Methods p3 | Dominica, West Indies | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 15.380620 | -61.41153 | 15.380620 | -61.41153 | Figure 1, site 8, converted to decimal using SB excel calculator | 29.12500 | Averaged from Results Sea Temperature p6 | NA | Atlantic Ocean | 29.14000 | 29.1400 | 0.2899137 | 10 | 11 | 28.67600 | 28.525 | 0.2093630 | aut | 10 | fall | NA | NA | NA | 1.32000 | 16 | Results p3 | 1416 | 1 | NA | Line | 132 | 10.0000 | 1.00 | 10.0000 | Results p3, Methods p3 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5164490 | 301.60 | 9.275682 |
| 30 | EI0030 | CD010 | SI011 | 22.0833300 | % | 1.66667 | Figure 6b, Metadigitise | 2004 | 0 | 0 | Figure 6b | Upper Florida Keys, USA | Materials and Methods Survey methods p370 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123610 | -80.29736 | 25.123610 | -80.29736 | Table 1, Key Largo Dry Rocks, converted using SB excel calculator | NA | NA | NA | Atlantic Ocean | 29.47300 | 29.4730 | NA | 7 | 7 | 29.14867 | 29.473 | 0.7002977 | sum | 7 | summer | 6.2360960 | NA | NA | 0.15000 | 5 | Materials and Methods Survey methods p370 | 556 | 0 | NA | Circle | 15 | NA | NA | 10.0000 | Materials and Methods Survey methods p370-372, plots are circular | NA | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.2314301 | 302.72 | 0.000000 |
| 31 | EI0031 | CD010 | SI011 | 30.6250000 | % | 1.875 | Figure 6b, Metadigitise | 2005 | 0 | 0 | Figure 6b | Upper Florida Keys, USA | Materials and Methods Survey methods p370 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123610 | -80.29736 | 25.123610 | -80.29736 | Table 1, Key Largo Dry Rocks, converted using SB excel calculator | NA | NA | NA | Atlantic Ocean | 28.97300 | 28.9730 | NA | 7 | 7 | 28.88633 | 28.973 | 1.1973554 | sum | 7 | summer | 7.0156080 | NA | NA | 0.15000 | 5 | Materials and Methods Survey methods p370 | 468 | 0 | NA | Circle | 15 | NA | NA | 10.0000 | Materials and Methods Survey methods p370-372, plots are circular | NA | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 1.2357025 | 302.72 | 1.048555 |
| 32 | EI0032 | CD010 | SI011 | 10.6250000 | % | 1.25 | Figure 6b, Metadigitise | 2006 | 0 | 0 | Figure 6b | Upper Florida Keys, USA | Materials and Methods Survey methods p370 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123610 | -80.29736 | 25.123610 | -80.29736 | Table 1, Key Largo Dry Rocks, converted using SB excel calculator | NA | NA | NA | Atlantic Ocean | 28.92800 | 28.9280 | NA | 7 | 7 | 28.82200 | 28.928 | 0.8609082 | sum | 7 | summer | 4.6770720 | NA | NA | 0.15000 | 5 | Materials and Methods Survey methods p370 | 373 | 0 | NA | Circle | 15 | NA | NA | 10.0000 | Materials and Methods Survey methods p370-372, plots are circular | NA | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.3421478 | 302.72 | 3.682837 |
| 33 | EI0033 | CD010 | SI011 | 11.8750000 | % | 1.66667 | Figure 6b, Metadigitise | 2007 | 0 | 0 | Figure 6b | Upper Florida Keys, USA | Materials and Methods Survey methods p370 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123610 | -80.29736 | 25.123610 | -80.29736 | Table 1, Key Largo Dry Rocks, converted using SB excel calculator | NA | NA | NA | Atlantic Ocean | 29.48000 | 29.4800 | NA | 7 | 7 | 29.04033 | 29.480 | 1.1145572 | sum | 7 | summer | 6.2360960 | NA | NA | 0.15000 | 5 | Materials and Methods Survey methods p370 | 337 | 0 | NA | Circle | 15 | NA | NA | 10.0000 | Materials and Methods Survey methods p370-372, plots are circular | NA | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 1.0682373 | 302.72 | 0.000000 |
| 34 | EI0034 | CD010 | SI011 | 17.5000000 | % | 2.08333 | Figure 6b, Metadigitise | 2008 | 0 | 0 | Figure 6b | Upper Florida Keys, USA | Materials and Methods Survey methods p370 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123610 | -80.29736 | 25.123610 | -80.29736 | Table 1, Key Largo Dry Rocks, converted using SB excel calculator | NA | NA | NA | Atlantic Ocean | 28.87800 | 28.8780 | NA | 7 | 7 | 28.79367 | 28.878 | 0.8247400 | sum | 7 | summer | 7.7951200 | NA | NA | 0.15000 | 5 | Materials and Methods Survey methods p370 | 318 | 0 | NA | Circle | 15 | NA | NA | 10.0000 | Materials and Methods Survey methods p370-372, plots are circular | NA | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.7328186 | 302.72 | 4.457100 |
| 35 | EI0035 | CD010 | SI011 | 17.5000000 | % | 2.08333 | Figure 6b, Metadigitise | 2009 | 0 | 0 | Figure 6b | Upper Florida Keys, USA | Materials and Methods Survey methods p370 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.123610 | -80.29736 | 25.123610 | -80.29736 | Table 1, Key Largo Dry Rocks, converted using SB excel calculator | NA | NA | NA | Atlantic Ocean | 29.38500 | 29.3850 | NA | 7 | 7 | 29.08367 | 29.385 | 0.9514864 | sum | 7 | summer | 7.7951200 | NA | NA | 0.15000 | 5 | Materials and Methods Survey methods p370 | 298 | 0 | NA | Circle | 15 | NA | NA | 10.0000 | Materials and Methods Survey methods p370-372, plots are circular | NA | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.2935791 | 302.72 | 0.000000 |
| 36 | EI0036 | CD044 | SI012 | 3.5600000 | % | NA | p1407 | 2014 | Sep | Sep | p1407 | Vaan Island, Gulf of Mannar | p1407 | Eastern Indian Ocean | Central Indian | 8.833330 | 78.21667 | 8.833330 | 78.21667 | p1407, GoogleMaps | NA | NA | NA | Indian Ocean | 27.95000 | 27.9500 | NA | 9 | 9 | 28.11700 | 27.950 | 0.4893596 | aut | 9 | fall | 1.2600000 | NA | NA | 0.24000 | 1 | p1407 | NA | 0 | NA | Line | 12 | 20.0000 | 1.00 | 20.0000 | p1407 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4628754 | 303.61 | 0.000000 |
| 39 | EI0042 | CD014 | SI015 | 71.9424460 | % | 28.41726619 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Sumilon Island East | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.295181 | 123.38678 | 9.295181 | 123.38678 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 49.2201489 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5528564 | 302.19 | 0.000000 |
| 40 | EI0043 | CD014 | SI015 | 55.0359712 | % | 7.73381295 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Sumilon Island West | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.295181 | 123.38678 | 9.295181 | 123.38678 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 13.3953570 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5528564 | 302.19 | 0.000000 |
| 41 | EI0044 | CD014 | SI016 | 44.9640288 | % | 4.67625899 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | North Bais Bay | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.636538 | 123.22198 | 9.636538 | 123.22198 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 8.0995182 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5439224 | 302.17 | 7.349969 |
| 42 | EI0045 | CD014 | SI016 | 20.6834532 | % | 8.63309353 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Bato, Cebu | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.636538 | 123.22198 | 9.636538 | 123.22198 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 14.9529566 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5439224 | 302.17 | 7.349969 |
| 43 | EI0046 | CD014 | SI015 | 14.0287770 | % | 9.71223022 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Cogon Reef and Marine Reserve | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.295181 | 123.38678 | 9.295181 | 123.38678 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 16.8220762 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5528564 | 302.19 | 0.000000 |
| 44 | EI0047 | CD014 | SI016 | 10.9712230 | % | 1.43884892 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Bolisong, Negros Oriental | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.636538 | 123.22198 | 9.636538 | 123.22198 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 2.4921594 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5439224 | 302.17 | 7.349969 |
| 45 | EI0048 | CD014 | SI016 | 10.4316547 | % | 7.1942446 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | South Bais Bay | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.636538 | 123.22198 | 9.636538 | 123.22198 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 12.4607972 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5439224 | 302.17 | 7.349969 |
| 46 | EI0049 | CD014 | SI015 | 8.2733813 | % | 11.51079137 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Cangalwang, Siquijor Island | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.295181 | 123.38678 | 9.295181 | 123.38678 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 19.9372755 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5528564 | 302.19 | 0.000000 |
| 47 | EI0050 | CD014 | SI015 | 0.0000000 | % | 0 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Apo Island | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.295181 | 123.38678 | 9.295181 | 123.38678 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 0.0000000 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5528564 | 302.19 | 0.000000 |
| 48 | EI0051 | CD014 | SI015 | 0.0000000 | % | 0 | Figure 5 | 1998 | Feb, Apr, Jun, Aug, Oct, Dec | Feb, Apr, Jun, Aug, Oct, Dec | Materials and Methods p97 | Bantayan, Negros Oriental | Figure 5 | Coral Triangle & SE Asia | Southeast Asia | 9.295181 | 123.38678 | 9.295181 | 123.38678 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, Location from centralized location | Pacific Ocean | 29.29382 | 30.2280 | 1.0311239 | 2 | 12 | 30.21200 | 30.228 | 0.0920494 | multi | 2 | winter | 0.0000000 | NA | NA | 0.75000 | 1 | Figure 5 | NA | 1 | 1 site stated because the effect sizes are split by site for this paper | Belt | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p97 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5528564 | 302.19 | 0.000000 |
| 49 | EI0052 | CD017 | SI017 | 14.2000000 | % | NA | Table 1 | 2005 | May | May | Methods 2.2 Disease prevalence and incidence p2 | Northwestern Hawaiian Islands | Methods 2.1 Description of sites p2 | Western Pacific | Polynesia | 23.833333 | -166.16667 | 23.833333 | -166.16667 | Methods 2.1 Description of sites p2, GoogleMaps | NA | NA | NA | Pacific Ocean | 25.18800 | 25.1880 | NA | 5 | 5 | 26.76333 | 26.670 | 0.4080845 | spr | 5 | spring | NA | NA | NA | 1.20000 | 1 | Methods 2.1 Description of sites p2 | 183 | 0 | Only one species identified at site | Belt | 2 | 25.0000 | 6.00 | 150.0000 | Methods 2.2 Disease prevalence and incidence p2, ran out of time, so estimated prevalence based on 25 x 2m transect | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2250061 | 300.18 | 0.000000 |
| 50 | EI0053 | CD017 | SI017 | 8.7430000 | % | NA | Table 1 | 2006 | May | May | Methods 2.2 Disease prevalence and incidence p2 | Northwestern Hawaiian Islands | Methods 2.1 Description of sites p2 | Western Pacific | Polynesia | 23.833333 | -166.16667 | 23.833333 | -166.16667 | Methods 2.1 Description of sites p2, GoogleMaps | NA | NA | NA | Pacific Ocean | 24.59500 | 24.5950 | NA | 5 | 5 | 26.50700 | 26.500 | 0.4425416 | spr | 5 | spring | NA | NA | NA | 1.20000 | 1 | Methods 2.1 Description of sites p2 | 183 | 0 | Only one species identified at site | Belt | 2 | 25.0000 | 6.00 | 150.0000 | Methods 2.2 Disease prevalence and incidence p2, ran out of time, so estimated prevalence based on 25 x 2m transect | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2428436 | 300.18 | 0.000000 |
| 51 | EI0054 | CD017 | SI018 | 4.2000000 | % | NA | Table 1 | 2008 | Jun | Jun | Methods 2.2 Disease prevalence and incidence p2 | American Samoa | Methods 2.1 Description of sites p2 | Western Pacific | Polynesia | -14.233333 | -170.66667 | -14.233333 | -170.66667 | Methods 2.1 Description of sites p2, GoogleMaps | NA | NA | NA | Pacific Ocean | 28.34500 | 28.3450 | NA | 6 | 6 | 29.18767 | 29.258 | 0.0804130 | win | 12 | winter | NA | NA | NA | 1.20000 | 1 | Methods 2.1 Description of sites p2 | 309 | 1 | NA | Belt | 2 | 25.0000 | 6.00 | 150.0000 | Methods 2.2 Disease prevalence and incidence p2, ran out of time, so estimated prevalence based on 25 x 2m transect | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3707581 | 302.08 | 0.000000 |
| 52 | EI0055 | CD017 | SI018 | 1.2940000 | % | NA | Table 1 | 2009 | Sep | Sep | Methods 2.2 Disease prevalence and incidence p2 | American Samoa | Methods 2.1 Description of sites p2 | Western Pacific | Polynesia | -14.233333 | -170.66667 | -14.233333 | -170.66667 | Methods 2.1 Description of sites p2, GoogleMaps | NA | NA | NA | Pacific Ocean | 27.66000 | 27.6600 | NA | 9 | 9 | 29.06534 | 29.453 | 0.3422513 | spr | 3 | spring | NA | NA | NA | 1.20000 | 1 | Methods 2.1 Description of sites p2 | 309 | 1 | NA | Belt | 2 | 25.0000 | 6.00 | 150.0000 | Methods 2.2 Disease prevalence and incidence p2, ran out of time, so estimated prevalence based on 25 x 2m transect | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3800049 | 302.08 | 2.175695 |
| 56 | EI0059 | CD019 | SI022 | 0.2700000 | % | 0.08 | Results Distribution, prevalence, and seasonality of MWS p4 | 2006 | Sep | Sep | Materials and Methods Distribution, prevalence, and seasonality of MWS p2 | Kaneohe Bay, Oahu, HI | Materials and Methods Study site p2 | Western Pacific | Polynesia | 21.464469 | -157.81539 | 21.464469 | -157.81539 | GoogleMaps | NA | NA | NA | Pacific Ocean | 26.71300 | 26.7130 | NA | 9 | 9 | 25.83500 | 25.880 | 0.4890554 | aut | 9 | fall | NA | NA | NA | 1.35000 | 9 | Materials and Methods Distribution, prevalence, and seasonality of MWS p2 | NA | 0 | NA | Belt | 2 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Distribution, prevalence, and seasonality of MWS p2 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.0814362 | 300.02 | 0.000000 |
| 57 | EI0060 | CD019 | SI022 | 0.3500000 | % | 0.13 | Results Distribution, prevalence, and seasonality of MWS p4 | 2007 | May | May | Materials and Methods Distribution, prevalence, and seasonality of MWS p2 | Kaneohe Bay, Oahu, HI | Materials and Methods Study site p2 | Western Pacific | Polynesia | 21.464469 | -157.81539 | 21.464469 | -157.81539 | GoogleMaps | NA | NA | NA | Pacific Ocean | 25.00000 | 25.0000 | NA | 5 | 5 | 25.96267 | 25.940 | 0.3295856 | spr | 5 | spring | NA | NA | NA | 1.35000 | 9 | Materials and Methods Distribution, prevalence, and seasonality of MWS p2 | NA | 0 | NA | Belt | 2 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Distribution, prevalence, and seasonality of MWS p2 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6685486 | 300.02 | 0.000000 |
| 58 | EI0061 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Carmelitas North, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 59 | EI0062 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Carmelitas South, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 60 | EI0063 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mujeres West, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 61 | EI0064 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mujeres East, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 62 | EI0065 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Carbinero, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 63 | EI0066 | CD022 | SI023 | 1.8987342 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Carmelitas North, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 64 | EI0067 | CD022 | SI023 | 2.6582278 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Carmelitas South, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 65 | EI0068 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mujeres West, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 66 | EI0069 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mujeres East, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 67 | EI0070 | CD022 | SI023 | 0.0000000 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Carbinero, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 68 | EI0071 | CD022 | SI023 | 15.0632911 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Carmelitas North, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 69 | EI0072 | CD022 | SI023 | 49.6202532 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Carmelitas South, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 70 | EI0073 | CD022 | SI023 | 19.1139241 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Mujeres West, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 71 | EI0074 | CD022 | SI023 | 6.2025316 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Mujeres East, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 72 | EI0075 | CD022 | SI023 | 1.3924051 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Carbinero, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 73 | EI0076 | CD022 | SI023 | 26.0759494 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Carmelitas North, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 74 | EI0077 | CD022 | SI023 | 58.4810127 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Carmelitas South, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 75 | EI0078 | CD022 | SI023 | 18.1012658 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mujeres West, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 76 | EI0079 | CD022 | SI023 | 9.3670886 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mujeres East, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 77 | EI0080 | CD022 | SI023 | 2.1518987 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Carbinero, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 78 | EI0081 | CD022 | SI023 | 24.8101266 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Carmelitas North, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 79 | EI0082 | CD022 | SI023 | 54.5569620 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Carmelitas South, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 80 | EI0083 | CD022 | SI023 | 18.3544304 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mujeres West, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 81 | EI0084 | CD022 | SI023 | 10.8860759 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mujeres East, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 82 | EI0085 | CD022 | SI023 | 3.5443038 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Carbinero, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 83 | EI0086 | CD022 | SI023 | 15.4430380 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Carmelitas North, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 84 | EI0087 | CD022 | SI023 | 39.3670886 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Carmelitas South, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 85 | EI0088 | CD022 | SI023 | 13.9240506 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mujeres West, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 86 | EI0089 | CD022 | SI023 | 15.8227848 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mujeres East, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 87 | EI0090 | CD022 | SI023 | 3.6708861 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Carbinero, Mona Island, Puerto Rico | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.078674 | -67.89264 | 18.078674 | -67.89264 | GoogleMaps for Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 2 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 3.14000 | 5 | Materials and Methods p68 | 2166 | 1 | Data aggregated for whole study | Circle | 2 | 20.0000 | NA | 314.0000 | Materials and Methods p68 | length = diameter, more a “site” than a transect | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 88 | EI0091 | CD026 | SI024 | 0.3800000 | % | 0.1 | Results p1039 | 2007 | Nov | Nov | Results p1039 | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | GA | Pacific Ocean | 25.44300 | 25.4430 | NA | 11 | 11 | 27.12033 | 27.273 | 0.2044906 | spr | 5 | spring | NA | NA | NA | 0.64500 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 7 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037, only 43 transects conducted this year | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6199951 | 300.27 | 0.000000 |
| 89 | EI0092 | CD026 | SI024 | 0.1200000 | % | 0.05 | Figure 3b | 2007 | Nov | Nov | Figure 3b | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | BrB Prevalence extracted using MetaDigitise in Rstudio, sample size 43 | Pacific Ocean | 25.44300 | 25.4430 | NA | 11 | 11 | 27.12033 | 27.273 | 0.2044906 | spr | 5 | spring | 0.3278719 | NA | NA | 0.64500 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 7 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037, only 43 transects conducted this year | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6199951 | 300.27 | 0.000000 |
| 90 | EI0093 | CD026 | SI024 | 1.1200000 | % | 0.31 | Results p1038 | 2007 | Nov | Nov | Results p1038 | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | UWS | Pacific Ocean | 25.44300 | 25.4430 | NA | 11 | 11 | 27.12033 | 27.273 | 0.2044906 | spr | 5 | spring | NA | NA | NA | 0.64500 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 7 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037, only 43 transects conducted this year | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6199951 | 300.27 | 0.000000 |
| 91 | EI0094 | CD026 | SI024 | 0.1300000 | % | 0.08 | Figure 3b | 2008 | Jan | Jan | Figure 3b | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | BrB Prevalence extracted using MetaDigitise in Rstudio, sample size 48 | Pacific Ocean | 27.27300 | 27.2730 | NA | 1 | 1 | 27.26767 | 27.258 | 0.1377544 | sum | 7 | summer | 0.5542563 | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6199951 | 300.27 | 0.000000 |
| 92 | EI0095 | CD026 | SI024 | 2.6700000 | % | 0.52 | Results p1038 | 2008 | Jan | Jan | Results p1038 | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | UWS | Pacific Ocean | 27.27300 | 27.2730 | NA | 1 | 1 | 27.26767 | 27.258 | 0.1377544 | sum | 7 | summer | NA | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6199951 | 300.27 | 0.000000 |
| 93 | EI0096 | CD026 | SI024 | 3.2900000 | % | 0.58 | Results p1038 | 2008 | Aug | Aug | Results p1038 | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | BrB | Pacific Ocean | 21.73800 | 21.7380 | NA | 8 | 8 | 27.26767 | 27.258 | 0.1377544 | win | 2 | winter | NA | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2974930 | 300.27 | 0.000000 |
| 94 | EI0097 | CD026 | SI024 | 0.0900000 | % | 0.05 | Figure 3b | 2008 | Aug | Aug | Figure 3b | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | UWS Prevalence extracted using MetaDigitise in Rstudio, sample size 48 | Pacific Ocean | 21.73800 | 21.7380 | NA | 8 | 8 | 27.26767 | 27.258 | 0.1377544 | win | 2 | winter | 0.3464102 | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2974930 | 300.27 | 0.000000 |
| 95 | EI0098 | CD026 | SI024 | 0.1400000 | % | 0.11 | Figure 3b | 2009 | Jan | Jan | Figure 3b | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | BrB Prevalence extracted using MetaDigitise in Rstudio, sample size 48 | Pacific Ocean | 27.25800 | 27.2580 | NA | 1 | 1 | 27.63767 | 27.765 | 0.4255358 | sum | 7 | summer | 0.7621024 | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3821106 | 300.27 | 0.000000 |
| 96 | EI0099 | CD026 | SI024 | 0.8600000 | % | 0.37 | Figure 3b | 2009 | Jan | Jan | Figure 3b | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | UWS Prevalence extracted using MetaDigitise in Rstudio, sample size 48 | Pacific Ocean | 27.25800 | 27.2580 | NA | 1 | 1 | 27.63767 | 27.765 | 0.4255358 | sum | 7 | summer | 2.5634352 | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3821106 | 300.27 | 0.000000 |
| 97 | EI0100 | CD026 | SI024 | 0.8200000 | % | 0.14 | Results p1039 | 2009 | Aug | Aug | Results p1039 | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | GA | Pacific Ocean | 22.01800 | 22.0180 | NA | 8 | 8 | 27.63767 | 27.765 | 0.4255358 | win | 2 | winter | NA | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6585693 | 300.27 | 0.000000 |
| 98 | EI0101 | CD026 | SI024 | 1.5300000 | % | 0.28 | Results p1038 | 2009 | Aug | Aug | Results p1038 | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | BrB | Pacific Ocean | 22.01800 | 22.0180 | NA | 8 | 8 | 27.63767 | 27.765 | 0.4255358 | win | 2 | winter | NA | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6585693 | 300.27 | 0.000000 |
| 99 | EI0102 | CD026 | SI024 | 0.3200000 | % | 0.14 | Figure 3b | 2009 | Aug | Aug | Figure 3b | Heron Island | Figure 1 | Western Pacific | Australia | -23.449452 | 151.97768 | -23.449452 | 151.97768 | GoogleMaps for Heron Reef | NA | NA | UWS Prevalence extracted using MetaDigitise in Rstudio, sample size 48 | Pacific Ocean | 22.01800 | 22.0180 | NA | 8 | 8 | 27.63767 | 27.765 | 0.4255358 | win | 2 | winter | 0.9699484 | NA | NA | 0.72000 | 6 | Figure 1 | 36030 | 1 | CoralNum aggregated for whole study, other metrics effect size specific | Belt | 8 | 15.0000 | 1.00 | 15.0000 | Methods Disease surveys p1037 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6585693 | 300.27 | 0.000000 |
| 100 | EI0103 | CD027 | SI025 | 1.4545455 | % | 0 | Figure 3 | 2008 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 27.95050 | 27.9505 | 0.7813540 | 2 | 3 | 28.25700 | 28.293 | 0.0821455 | aut | 8 | summer | 0.0000000 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6814270 | 301.97 | 0.000000 |
| 101 | EI0104 | CD027 | SI026 | 0.7272727 | % | 0 | Figure 3 | 2008 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 27.95050 | 27.9505 | 0.7813540 | 2 | 3 | 28.25700 | 28.293 | 0.0821455 | aut | 8 | summer | 0.0000000 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6814270 | 301.97 | 0.000000 |
| 102 | EI0105 | CD027 | SI025 | 4.3636364 | % | 1.45454545 | Figure 3 | 2008 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 23.17800 | 23.1780 | NA | 6 | 6 | 28.25700 | 28.293 | 0.0821455 | win | 12 | winter | 3.2524625 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9414368 | 301.97 | 0.000000 |
| 103 | EI0106 | CD027 | SI026 | 1.4545455 | % | 0.72727273 | Figure 3 | 2008 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 23.17800 | 23.1780 | NA | 6 | 6 | 28.25700 | 28.293 | 0.0821455 | win | 12 | winter | 1.6262313 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9414368 | 301.97 | 0.000000 |
| 104 | EI0107 | CD027 | SI025 | 63.8000000 | % | 3.03 | Results Disease dynamics and rainfall p819 | 2009 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 27.89800 | 27.8980 | 0.3747671 | 2 | 3 | 28.37600 | 28.318 | 0.3882630 | aut | 8 | summer | NA | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4192963 | 301.97 | 1.084291 |
| 105 | EI0108 | CD027 | SI026 | 60.6000000 | % | 3.8 | Results Disease dynamics and rainfall p819 | 2009 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 27.89800 | 27.8980 | 0.3747671 | 2 | 3 | 28.37600 | 28.318 | 0.3882630 | aut | 8 | summer | NA | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4192963 | 301.97 | 1.084291 |
| 106 | EI0109 | CD027 | SI025 | 0.7272727 | % | 0.36363636 | Figure 3 | 2009 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 23.68300 | 23.6830 | NA | 6 | 6 | 28.37600 | 28.318 | 0.3882630 | win | 12 | winter | 0.8131156 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4064484 | 301.97 | 2.084293 |
| 107 | EI1020 | CD027 | SI025 | 7.2727273 | % | 2.18181818 | Figure 3 | 2010 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 28.55750 | 28.5575 | 0.3288048 | 2 | 3 | 28.16433 | 28.245 | 0.0764288 | aut | 8 | summer | 4.8786938 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7428589 | 301.97 | 1.000002 |
| 108 | EI1021 | CD027 | SI025 | 0.0000000 | % | 0 | Figure 3 | 2010 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 23.78500 | 23.7850 | NA | 6 | 6 | 28.16433 | 28.245 | 0.0764288 | win | 12 | winter | 0.0000000 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.0157242 | 301.97 | 1.692842 |
| 109 | EI1022 | CD027 | SI025 | 1.4545455 | % | 4.72727273 | Figure 3 | 2011 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 28.07000 | 28.0700 | 0.1202082 | 2 | 3 | 28.25267 | 28.085 | 0.4288319 | aut | 8 | summer | 10.5705032 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6656952 | 301.97 | 3.241398 |
| 110 | EI1023 | CD027 | SI025 | 0.0000000 | % | 0 | Figure 3 | 2011 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Nelly Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.163570 | 146.85079 | -19.163570 | 146.85079 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 22.92500 | 22.9250 | NA | 6 | 6 | 28.25267 | 28.085 | 0.4288319 | win | 12 | winter | 0.0000000 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7796326 | 301.97 | 1.548555 |
| 111 | EI0110 | CD027 | SI026 | 1.4545455 | % | 0.72727273 | Figure 3 | 2009 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 23.68300 | 23.6830 | NA | 6 | 6 | 28.37600 | 28.318 | 0.3882630 | win | 12 | winter | 1.6262313 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4064484 | 301.97 | 2.084293 |
| 112 | EI1024 | CD027 | SI026 | 15.6363636 | % | 3.27272727 | Figure 3 | 2010 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 28.55750 | 28.5575 | 0.3288048 | 2 | 3 | 28.16433 | 28.245 | 0.0764288 | aut | 8 | summer | 7.3180407 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7428589 | 301.97 | 1.000002 |
| 113 | EI1025 | CD027 | SI026 | 0.0000000 | % | 0 | Figure 3 | 2010 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 23.78500 | 23.7850 | NA | 6 | 6 | 28.16433 | 28.245 | 0.0764288 | win | 12 | winter | 0.0000000 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.0157242 | 301.97 | 1.692842 |
| 114 | EI1026 | CD027 | SI026 | 23.6363636 | % | 0.36363636 | Figure 3 | 2011 | Feb-Mar | Feb-Mar | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 28.07000 | 28.0700 | 0.1202082 | 2 | 3 | 28.25267 | 28.085 | 0.4288319 | aut | 8 | summer | 0.8131156 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6656952 | 301.97 | 3.241398 |
| 115 | EI1027 | CD027 | SI026 | 0.0000000 | % | 0 | Figure 3 | 2011 | Jun | Jun | Methods Study sites and biannual disease surveys p816, Figure 3 | Geoffrey Bay, Magnetic Island | Methods Study sites and biannual disease surveys p816 | Western Pacific | Australia | -19.153980 | 146.86556 | -19.153980 | 146.86556 | Methods Study sites and biannual disease surveys p816, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, sample size 5 | Pacific Ocean | 22.92500 | 22.9250 | NA | 6 | 6 | 28.25267 | 28.085 | 0.4288319 | win | 12 | winter | 0.0000000 | NA | NA | 0.20000 | 1 | Methods Study sites and biannual disease surveys p816 | NA | 1 | Mixed Montipora sp | Belt | 5 | 20.0000 | 2.00 | 40.0000 | Methods Study sites and biannual disease surveys p817 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7796326 | 301.97 | 1.548555 |
| 116 | EI0111 | CD028 | SI027 | 0.4523810 | % | 6.87E-02 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Coral Gardens Reef Crest Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.1190476 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 117 | EI0112 | CD028 | SI027 | 0.0000000 | % | 0 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Coral Gardens Reef Flat Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 118 | EI0113 | CD028 | SI027 | 0.0000000 | % | 0 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Coral Gardens Reef Slope Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 119 | EI0114 | CD028 | SI027 | 0.0000000 | % | 0 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Hoga Buoy 2 Reef Crest Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 120 | EI0115 | CD028 | SI027 | 1.3095238 | % | 0.98974332 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Hoga Buoy 2 Reef Flat Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 1.7142857 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 121 | EI0116 | CD028 | SI027 | 0.0000000 | % | 0 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Hoga Buoy 2 Reef Slope Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 122 | EI0117 | CD028 | SI027 | 0.2380952 | % | 0.13746435 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Kaledupa 1 Reef Crest Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.2380952 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 123 | EI0118 | CD028 | SI027 | 2.7380952 | % | 1.05847549 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Kaledupa 1 Reef Flat Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 1.8333330 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 124 | EI0119 | CD028 | SI027 | 0.3095238 | % | 0.26118226 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Kaledupa 1 Reef Slope Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.4523810 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 125 | EI0120 | CD028 | SI027 | 0.5952381 | % | 0.316168 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Pak Kasims Reef Crest Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.5476190 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 126 | EI0121 | CD028 | SI027 | 0.4523810 | % | 8.25E-02 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Pak Kasims Reef Flat Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.1428571 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 127 | EI0122 | CD028 | SI027 | 0.1666667 | % | 0.15121078 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Pak Kasims Reef Slope Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.2619048 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 128 | EI0123 | CD028 | SI027 | 0.6190476 | % | 0.2749287 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Sampela Reef Crest Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.4761905 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 129 | EI0124 | CD028 | SI027 | 1.5476190 | % | 1.07222193 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Sampela Reef Flat Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 1.8571429 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 130 | EI0125 | CD028 | SI027 | 0.0000000 | % | 0 | Figure 8 | 2005 | Jun-Sep | Jun-Sep | Materials and Methods Study site p404 | Sampela Reef Slope Wakatobi Marine National Park | Materials and Methods Study site p404, Figure 8 | Coral Triangle & SE Asia | Southeast Asia | -5.563220 | 123.93047 | -5.563220 | 123.93047 | GoogleMaps Wakatobi National Park | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 27.89100 | 27.6180 | 0.3919173 | 6 | 9 | 29.31600 | 29.100 | 0.5752639 | win | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 15 | Figure 8 | 12352 | 1 | Coral number aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Survey method p404 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Study examines more diseases, but figure 8 where the effect size was extracted from only measured white syndrome | 1.1628494 | 302.42 | 1.210006 |
| 131 | EI0126 | CD029 | SI028 | 1.8974359 | % | 0.46153846 | Figure 3 | 2010 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Coral Gardens Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.80400 | 29.8040 | 0.3478969 | 10 | 11 | 28.98600 | 28.663 | 0.7007514 | spr | 4 | spring | 1.3846154 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4614258 | 302.43 | 4.509983 |
| 132 | EI0127 | CD029 | SI028 | 1.0000000 | % | 0.23076923 | Figure 3 | 2011 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Coral Gardens Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.02150 | 29.0215 | 0.9425735 | 10 | 11 | 29.14200 | 28.913 | 0.7049695 | spr | 4 | spring | 0.6923077 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9624863 | 302.43 | 4.128520 |
| 133 | EI0128 | CD029 | SI028 | 1.0769231 | % | 0.79487179 | Figure 3 | 2010 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Hoga Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.80400 | 29.8040 | 0.3478969 | 10 | 11 | 28.98600 | 28.663 | 0.7007514 | spr | 4 | spring | 2.3846154 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4614258 | 302.43 | 4.509983 |
| 134 | EI0129 | CD029 | SI028 | 0.3751051 | % | 0.15178669 | Figure 3 | 2011 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Hoga Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.02150 | 29.0215 | 0.9425735 | 10 | 11 | 29.14200 | 28.913 | 0.7049695 | spr | 4 | spring | 0.4553601 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9624863 | 302.43 | 4.128520 |
| 135 | EI0130 | CD029 | SI028 | 1.3465399 | % | 0.36428806 | Figure 3 | 2010 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Kaledupa Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.80400 | 29.8040 | 0.3478969 | 10 | 11 | 28.98600 | 28.663 | 0.7007514 | spr | 4 | spring | 1.0928642 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4614258 | 302.43 | 4.509983 |
| 136 | EI0131 | CD029 | SI028 | 0.3751051 | % | 0.12142935 | Figure 3 | 2011 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Kaledupa Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.02150 | 29.0215 | 0.9425735 | 10 | 11 | 29.14200 | 28.913 | 0.7049695 | spr | 4 | spring | 0.3642881 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9624863 | 302.43 | 4.128520 |
| 137 | EI0132 | CD029 | SI028 | 0.9670732 | % | 0.28839471 | Figure 3 | 2010 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Pak Kasims Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.80400 | 29.8040 | 0.3478969 | 10 | 11 | 28.98600 | 28.663 | 0.7007514 | spr | 4 | spring | 0.8651841 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4614258 | 302.43 | 4.509983 |
| 138 | EI0133 | CD029 | SI028 | 0.3902837 | % | 0.18214403 | Figure 3 | 2011 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Pak Kasims Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.02150 | 29.0215 | 0.9425735 | 10 | 11 | 29.14200 | 28.913 | 0.7049695 | spr | 4 | spring | 0.5464321 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9624863 | 302.43 | 4.128520 |
| 139 | EI0134 | CD029 | SI028 | 0.3751051 | % | 0.15178669 | Figure 3 | 2010 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Sampela Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.80400 | 29.8040 | 0.3478969 | 10 | 11 | 28.98600 | 28.663 | 0.7007514 | spr | 4 | spring | 0.4553601 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4614258 | 302.43 | 4.509983 |
| 140 | EI0135 | CD029 | SI028 | 0.7697505 | % | 0.24285871 | Figure 3 | 2011 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Sampela Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=9 | Pacific Ocean | 29.02150 | 29.0215 | 0.9425735 | 10 | 11 | 29.14200 | 28.913 | 0.7049695 | spr | 4 | spring | 0.7285761 | NA | NA | 0.72000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 9 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | NA | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9624863 | 302.43 | 4.128520 |
| 141 | EI0136 | CD029 | SI028 | 0.7242145 | % | 0.45536007 | Figure 3 | 2010 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Blue Bowl Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=6 | Pacific Ocean | 29.80400 | 29.8040 | 0.3478969 | 10 | 11 | 28.98600 | 28.663 | 0.7007514 | spr | 4 | spring | 1.1153998 | NA | NA | 0.14000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | Blue Bowl has no reef flat transects | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4614258 | 302.43 | 4.509983 |
| 142 | EI0137 | CD029 | SI028 | 5.0349565 | % | 3.09644851 | Figure 3 | 2011 | Oct-Nov | Oct-Nov | Materials and methods Study sites p949 | Blue Bowl Wakatobi Marine National Park | Figure 3 | Coral Triangle & SE Asia | Southeast Asia | -5.468610 | 123.74468 | -5.468610 | 123.74468 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=6 | Pacific Ocean | 29.02150 | 29.0215 | 0.9425735 | 10 | 11 | 29.14200 | 28.913 | 0.7049695 | spr | 4 | spring | 7.5847189 | NA | NA | 0.14000 | 6 | Materials and methods Study sites p949 | NA | 1 | NA | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and methods Survey method p949-950 | Blue Bowl has no reef flat transects | 9 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9624863 | 302.43 | 4.128520 |
| 143 | EI0138 | CD030 | SI029 | 14.5000000 | % | 4 | Results 3.1.1 Disease prevalence | 2011 | Sep | Sep | Methods Data collection | Koh Tau | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 10.103090 | 99.83952 | 10.103090 | 99.83952 | Figure 1, GoogleMaps | NA | NA | High use site | Pacific Ocean | 28.76500 | 28.7650 | NA | 9 | 9 | 29.13267 | 29.180 | 0.0433172 | aut | 9 | fall | NA | NA | NA | 0.45000 | 10 | Methods Data collection | 5983 | 1 | NA | Belt | 15 | 15.0000 | 2.00 | 30.0000 | Methods Data collection, Table 1 | NA | 4 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.8981934 | 303.28 | 0.000000 |
| 144 | EI0139 | CD030 | SI029 | 5.2000000 | % | 1.3 | Results 3.1.1 Disease prevalence | 2011 | Sep | Sep | Methods Data collection | Koh Tau | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 10.103090 | 99.83952 | 10.103090 | 99.83952 | Figure 1, GoogleMaps | NA | NA | Low use site | Pacific Ocean | 28.76500 | 28.7650 | NA | 9 | 9 | 29.13267 | 29.180 | 0.0433172 | aut | 9 | fall | NA | NA | NA | 0.45000 | 10 | Methods Data collection | 4516 | 1 | NA | Belt | 15 | 15.0000 | 2.00 | 30.0000 | Methods Data collection, Table 1 | NA | 4 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.8981934 | 303.28 | 0.000000 |
| 145 | EI0140 | CD031 | SI030 | 1.0000000 | % | 0.3 | Results 3a Influence of protected areas on coral disease following an acute disturbance | 2012 | Feb | Feb | Material and methods Study locations and protected areas management | Palm Island | Figure 1 | Western Pacific | Australia | -18.566667 | 146.48333 | -18.566667 | 146.48333 | Material and methods Study locations and protected areas management | NA | NA | Inside reserves | Pacific Ocean | 28.92800 | 28.9280 | NA | 2 | 2 | 28.38100 | 28.330 | 0.6599792 | sum | 8 | summer | NA | NA | NA | 2.34000 | 26 | Results 3a Influence of protected areas on coral disease following an acute disturbance | 36104 | 1 | Coral number aggregated from whole study | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Material and methods 2b Coral disease surveys and visual census of reef fishes | Transect number is per site | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7178421 | 301.94 | 0.000000 |
| 146 | EI0141 | CD031 | SI030 | 7.4000000 | % | 0.9 | Results 3a Influence of protected areas on coral disease following an acute disturbance | 2012 | Feb | Feb | Material and methods Study locations and protected areas management | Palm Island | Figure 1 | Western Pacific | Australia | -18.566667 | 146.48333 | -18.566667 | 146.48333 | Material and methods Study locations and protected areas management | NA | NA | Outside reserves | Pacific Ocean | 28.92800 | 28.9280 | NA | 2 | 2 | 28.38100 | 28.330 | 0.6599792 | sum | 8 | summer | NA | NA | NA | 2.34000 | 26 | Results 3a Influence of protected areas on coral disease following an acute disturbance | 36104 | 1 | Coral number aggregated from whole study | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Material and methods 2b Coral disease surveys and visual census of reef fishes | Transect number is per site | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7178421 | 301.94 | 0.000000 |
| 147 | EI0142 | CD031 | SI031 | 1.4000000 | % | 0.7 | Results 3b Influence of protected areas on coral disease following a chronic disturbance | 2013 | May | May | Material and methods Study locations and protected areas management | Keppel Islands | Figure 1 | Western Pacific | Australia | -23.166670 | 150.95000 | -23.166670 | 150.95000 | Material and methods Study locations and protected areas management | NA | NA | Inside reserves | Pacific Ocean | 24.49300 | 24.4930 | NA | 5 | 5 | 26.95367 | 27.350 | 0.4542198 | aut | 11 | fall | NA | NA | NA | 1.89000 | 21 | Results 3b Influence of protected areas on coral disease following a chronic disturbance | 36104 | 1 | Coral number aggregated from whole study | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Material and methods 2b Coral disease surveys and visual census of reef fishes | Transect number is per site | 3 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5424957 | 300.71 | 0.000000 |
| 148 | EI0143 | CD031 | SI031 | 3.4000000 | % | 1 | Results 3b Influence of protected areas on coral disease following a chronic disturbance | 2013 | May | May | Material and methods Study locations and protected areas management | Keppel Islands | Figure 1 | Western Pacific | Australia | -23.166670 | 150.95000 | -23.166670 | 150.95000 | Material and methods Study locations and protected areas management | NA | NA | Outside reserves | Pacific Ocean | 24.49300 | 24.4930 | NA | 5 | 5 | 26.95367 | 27.350 | 0.4542198 | aut | 11 | fall | NA | NA | NA | 1.89000 | 21 | Results 3b Influence of protected areas on coral disease following a chronic disturbance | 36104 | 1 | Coral number aggregated from whole study | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Material and methods 2b Coral disease surveys and visual census of reef fishes | Transect number is per site | 4 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5424957 | 300.71 | 0.000000 |
| 149 | EI0144 | CD032 | SI032 | 1.0000000 | % | 0.2 | Results Influence of marine protected areas on coral disease prevalence p2560 | 2012 | Oct-Nov | Oct-Nov | Methods Study location and protected areas management p2557 | Whitsunday Islands | Figure 1 | Western Pacific | Australia | -20.133330 | 148.93330 | -20.133330 | 148.93330 | Methods Study location and protected areas management p2556 | NA | NA | Reserves | Pacific Ocean | 25.08000 | 25.0800 | 1.1030862 | 10 | 11 | 27.72200 | 27.758 | 0.6667287 | spr | 4 | spring | NA | NA | NA | 1.89000 | 21 | Methods Study location and protected areas management p2557 | 80866 | 1 | Coral number aggregated from whole study | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Methods Coral health surveys p2257 | Transect number is per site | 6 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 301.33 | 2.504247 |
| 150 | EI0145 | CD032 | SI032 | 4.1000000 | % | 0.4 | Results Influence of marine protected areas on coral disease prevalence p2560 | 2012 | Oct-Nov | Oct-Nov | Methods Study location and protected areas management p2557 | Whitsunday Islands | Figure 1 | Western Pacific | Australia | -20.133330 | 148.93330 | -20.133330 | 148.93330 | Methods Study location and protected areas management p2556 | NA | NA | Non-reserve sites | Pacific Ocean | 25.08000 | 25.0800 | 1.1030862 | 10 | 11 | 27.72200 | 27.758 | 0.6667287 | spr | 4 | spring | NA | NA | NA | 1.80000 | 20 | Methods Study location and protected areas management p2557 | 80866 | 1 | Coral number aggregated from whole study | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Methods Coral health surveys p2257 | Transect number is per site | 6 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 301.33 | 2.504247 |
| 151 | EI0146 | CD033 | SI033 | 3.2700000 | % | 0.62 | Table 1 | 2009 | Jun-July | Jun-Jul | Methods Study sites and data collection p1046 | Great Barrier Reef Marine Park | Figure 1 | Western Pacific | Australia | -17.007790 | 152.16906 | -17.007790 | 152.16906 | Figure 1, GoogleMaps | NA | NA | With platform (high tourism); renamed months (removed y) to match format for data analysis | Pacific Ocean | 25.74800 | 25.7480 | 0.3535534 | 6 | 7 | 28.42933 | 28.373 | 0.4551227 | win | 12 | winter | NA | NA | NA | 0.72000 | 4 | Figure 1 | 7043 | 1 | NA | Belt | 24 | 15.0000 | 2.00 | 30.0000 | Methods Study sites and data collection p1047 | NA | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414001 | 301.28 | 9.218532 |
| 152 | EI0147 | CD033 | SI033 | 0.2100000 | % | 7.00E-02 | Table 1 | 2009 | Jun-July | Jun-Jul | Methods Study sites and data collection p1046 | Great Barrier Reef Marine Park | Figure 1 | Western Pacific | Australia | -17.007790 | 152.16906 | -17.007790 | 152.16906 | Figure 1, GoogleMaps | NA | NA | Without platform (low tourism); renamed months (removed y) to match format for data analysis | Pacific Ocean | 25.74800 | 25.7480 | 0.3535534 | 6 | 7 | 28.42933 | 28.373 | 0.4551227 | win | 12 | winter | NA | NA | NA | 0.63000 | 4 | Figure 1 | 9468 | 1 | NA | Belt | 21 | 15.0000 | 2.00 | 30.0000 | Methods Study sites and data collection p1047 | NA | 3 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414001 | 301.28 | 9.218532 |
| 153 | EI0148 | CD035 | SI034 | 0.0900000 | % | 0.04 | Results Distribution and spatial variability of BBD p45 | 2004 | Jan-Mar | Jan-Mar | Materials and Methods p43 | Great Barrier Reef - Gladstone to Cooktown | Figure 1 | Western Pacific | Australia | -18.420030 | 147.44867 | -18.420030 | 147.44867 | Figure 1, GoogleMaps Dip Reef | NA | NA | NA | Pacific Ocean | 29.11033 | 29.5280 | 0.4011693 | 1 | 3 | 28.33433 | 28.398 | 0.5801265 | sum | 7 | summer | NA | NA | NA | 2.28000 | 19 | Table 1 | 113747 | 1 | NA | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and Methods p43 | Transect number is per site | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9564285 | 301.61 | 0.000000 |
| 154 | EI0149 | CD036 | SI035 | 2.2900000 | % | 0.45 | Table 3 | 2005 | Jan | Jan | Materials and Methods Quantifying coral disease and coral community structure p137 | Palau | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 7.337981 | 134.55450 | 7.337981 | 134.55450 | Figure 1, GoogleMaps Palau | NA | NA | MPA | Pacific Ocean | 28.28300 | 28.2830 | NA | 1 | 1 | 29.08100 | 29.228 | 0.3747839 | win | 1 | winter | NA | NA | NA | 0.96000 | 8 | Materials and Methods Quantifying coral disease and coral community structure p137 | NA | 1 | NA | Belt | 24 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Quantifying coral disease and coral community structure p138 | NA | 3 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2271423 | 302.40 | 0.000000 |
| 155 | EI0150 | CD036 | SI035 | 1.8300000 | % | 0.44 | Table 3 | 2005 | Jan | Jan | Materials and Methods Quantifying coral disease and coral community structure p137 | Palau | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 7.337981 | 134.55450 | 7.337981 | 134.55450 | Figure 1, GoogleMaps Palau | NA | NA | Control | Pacific Ocean | 28.28300 | 28.2830 | NA | 1 | 1 | 29.08100 | 29.228 | 0.3747839 | win | 1 | winter | NA | NA | NA | 0.96000 | 8 | Materials and Methods Quantifying coral disease and coral community structure p137 | NA | 1 | NA | Belt | 24 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Quantifying coral disease and coral community structure p138 | NA | 3 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2271423 | 302.40 | 0.000000 |
| 156 | EI0151 | CD037 | SI036 | 6.9767440 | % | NA | Figure 2 | 2004 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 26.87984 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.12800 | 28.1280 | NA | 10 | 10 | 29.64467 | 29.963 | 0.6671268 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 157 | EI0152 | CD037 | SI036 | 6.5116280 | % | NA | Figure 2 | 2004 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 25.97700 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.12800 | 28.1280 | NA | 10 | 10 | 29.64467 | 29.963 | 0.6671268 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 158 | EI0153 | CD037 | SI036 | 6.3105680 | % | NA | Figure 2 | 2004 | Nov | Nov | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 26.87984 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 26.81300 | 26.8130 | NA | 11 | 11 | 29.64467 | 29.963 | 0.6671268 | aut | 11 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 159 | EI0154 | CD037 | SI036 | 4.7778520 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 21.31235 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 160 | EI0155 | CD037 | SI036 | 2.6463630 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 20.40951 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 161 | EI0156 | CD037 | SI036 | 5.6304480 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 22.36566 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 162 | EI0157 | CD037 | SI036 | 6.9093410 | % | NA | Figure 2 | 2005 | Apr | Apr | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 23.11802 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 24.76000 | 24.7600 | NA | 4 | 4 | 29.42034 | 29.525 | 1.0588871 | spr | 4 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7864532 | 302.82 | 3.788568 |
| 163 | EI0158 | CD037 | SI036 | 2.6463630 | % | NA | Figure 2 | 2005 | Aug | Aug | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.69496 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 30.42300 | 30.4230 | NA | 8 | 8 | 29.42034 | 29.525 | 1.0588871 | sum | 8 | summer | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7957153 | 302.82 | 3.902856 |
| 164 | EI0159 | CD037 | SI036 | 1.3674700 | % | NA | Figure 2 | 2005 | Aug | Aug | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.69496 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 30.42300 | 30.4230 | NA | 8 | 8 | 29.42034 | 29.525 | 1.0588871 | sum | 8 | summer | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7957153 | 302.82 | 3.902856 |
| 165 | EI0160 | CD037 | SI036 | 1.3674700 | % | NA | Figure 2 | 2005 | Sep | Sep | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.24354 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 29.67500 | 29.6750 | NA | 9 | 9 | 29.42034 | 29.525 | 1.0588871 | aut | 9 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 166 | EI0161 | CD037 | SI036 | 2.2200660 | % | NA | Figure 2 | 2005 | Sep | Sep | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 30.34071 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 29.67500 | 29.6750 | NA | 9 | 9 | 29.42034 | 29.525 | 1.0588871 | aut | 9 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 167 | EI0162 | CD037 | SI036 | 9.8934260 | % | NA | Figure 2 | 2005 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 29.28740 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.43800 | 28.4380 | NA | 10 | 10 | 29.42034 | 29.525 | 1.0588871 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 168 | EI0163 | CD037 | SI036 | 14.1564030 | % | NA | Figure 2 | 2005 | Nov | Nov | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 25.37511 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 26.46800 | 26.4680 | NA | 11 | 11 | 29.42034 | 29.525 | 1.0588871 | aut | 11 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 169 | EI0164 | CD037 | SI036 | 6.0567460 | % | NA | Figure 2 | 2006 | Mar | Mar | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 22.66660 | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 24.15500 | 24.1550 | NA | 3 | 3 | 29.26933 | 29.395 | 0.7494438 | spr | 3 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8278503 | 302.82 | 5.594270 |
| 170 | EI0165 | CD037 | SI036 | 7.7619370 | % | NA | Figure 2 | 2006 | Apr | Apr | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | NA | Figure 2 | White plague; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 25.32500 | 25.3250 | NA | 4 | 4 | 29.26933 | 29.395 | 0.7494438 | spr | 4 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 96 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8278503 | 302.82 | 5.594270 |
| 171 | EI0166 | CD037 | SI036 | 1.5400055 | % | NA | Figure 2 | 2004 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 26.87984 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.12800 | 28.1280 | NA | 10 | 10 | 29.64467 | 29.963 | 0.6671268 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 172 | EI0167 | CD037 | SI036 | 0.7122093 | % | NA | Figure 2 | 2004 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 25.97700 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.12800 | 28.1280 | NA | 10 | 10 | 29.64467 | 29.963 | 0.6671268 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 173 | EI0168 | CD037 | SI036 | 1.5400055 | % | NA | Figure 2 | 2004 | Nov | Nov | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 26.87984 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 26.81300 | 26.8130 | NA | 11 | 11 | 29.64467 | 29.963 | 0.6671268 | aut | 11 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 174 | EI0169 | CD037 | SI036 | 2.3678018 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 21.31235 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 175 | EI0170 | CD037 | SI036 | 1.5400055 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 20.40951 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 176 | EI0171 | CD037 | SI036 | 1.5400055 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 22.36566 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 177 | EI0172 | CD037 | SI036 | 1.5400055 | % | NA | Figure 2 | 2005 | Apr | Apr | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 23.11802 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 24.76000 | 24.7600 | NA | 4 | 4 | 29.42034 | 29.525 | 1.0588871 | spr | 4 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7864532 | 302.82 | 3.788568 |
| 178 | EI0173 | CD037 | SI036 | 4.8511905 | % | NA | Figure 2 | 2005 | Aug | Aug | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.69496 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 30.42300 | 30.4230 | NA | 8 | 8 | 29.42034 | 29.525 | 1.0588871 | sum | 8 | summer | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7957153 | 302.82 | 3.902856 |
| 179 | EI0174 | CD037 | SI036 | 7.3345792 | % | NA | Figure 2 | 2005 | Aug | Aug | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.69496 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 30.42300 | 30.4230 | NA | 8 | 8 | 29.42034 | 29.525 | 1.0588871 | sum | 8 | summer | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7957153 | 302.82 | 3.902856 |
| 180 | EI0175 | CD037 | SI036 | 6.9206811 | % | NA | Figure 2 | 2005 | Sep | Sep | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.24354 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 29.67500 | 29.6750 | NA | 9 | 9 | 29.42034 | 29.525 | 1.0588871 | aut | 9 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 181 | EI0176 | CD037 | SI036 | 6.5067829 | % | NA | Figure 2 | 2005 | Sep | Sep | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 30.34071 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 29.67500 | 29.6750 | NA | 9 | 9 | 29.42034 | 29.525 | 1.0588871 | aut | 9 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 182 | EI0177 | CD037 | SI036 | 5.6789867 | % | NA | Figure 2 | 2005 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 29.28740 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.43800 | 28.4380 | NA | 10 | 10 | 29.42034 | 29.525 | 1.0588871 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 183 | EI0178 | CD037 | SI036 | 4.0233942 | % | NA | Figure 2 | 2005 | Nov | Nov | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 25.37511 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 26.46800 | 26.4680 | NA | 11 | 11 | 29.42034 | 29.525 | 1.0588871 | aut | 11 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 184 | EI0179 | CD037 | SI036 | 0.2983112 | % | NA | Figure 2 | 2006 | Mar | Mar | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 22.66660 | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 24.15500 | 24.1550 | NA | 3 | 3 | 29.26933 | 29.395 | 0.7494438 | spr | 3 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8278503 | 302.82 | 5.594270 |
| 185 | EI0180 | CD037 | SI036 | 0.2983112 | % | NA | Figure 2 | 2006 | Apr | Apr | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | NA | Figure 2 | Dark spot; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 25.32500 | 25.3250 | NA | 4 | 4 | 29.26933 | 29.395 | 0.7494438 | spr | 4 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 172 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8278503 | 302.82 | 5.594270 |
| 186 | EI0181 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2004 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 26.87984 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.12800 | 28.1280 | NA | 10 | 10 | 29.64467 | 29.963 | 0.6671268 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 187 | EI0182 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2004 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 25.97700 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.12800 | 28.1280 | NA | 10 | 10 | 29.64467 | 29.963 | 0.6671268 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 188 | EI0183 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2004 | Nov | Nov | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 26.87984 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 26.81300 | 26.8130 | NA | 11 | 11 | 29.64467 | 29.963 | 0.6671268 | aut | 11 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0271301 | 302.82 | 3.788568 |
| 189 | EI0184 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 21.31235 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 190 | EI0185 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 20.40951 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 191 | EI0186 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2005 | Feb | Feb | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 22.36566 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 23.40500 | 23.4050 | NA | 2 | 2 | 29.42034 | 29.525 | 1.0588871 | win | 2 | winter | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2014542 | 302.82 | 3.788568 |
| 192 | EI0187 | CD037 | SI036 | 0.0000000 | % | NA | Figure 2 | 2005 | Apr | Apr | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 23.11802 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 24.76000 | 24.7600 | NA | 4 | 4 | 29.42034 | 29.525 | 1.0588871 | spr | 4 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7864532 | 302.82 | 3.788568 |
| 193 | EI0188 | CD037 | SI036 | 2.3809520 | % | NA | Figure 2 | 2005 | Aug | Aug | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.69496 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 30.42300 | 30.4230 | NA | 8 | 8 | 29.42034 | 29.525 | 1.0588871 | sum | 8 | summer | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7957153 | 302.82 | 3.902856 |
| 194 | EI0189 | CD037 | SI036 | 4.2857140 | % | NA | Figure 2 | 2005 | Aug | Aug | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.69496 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 30.42300 | 30.4230 | NA | 8 | 8 | 29.42034 | 29.525 | 1.0588871 | sum | 8 | summer | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7957153 | 302.82 | 3.902856 |
| 195 | EI0190 | CD037 | SI036 | 6.1904760 | % | NA | Figure 2 | 2005 | Sep | Sep | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 31.24354 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 29.67500 | 29.6750 | NA | 9 | 9 | 29.42034 | 29.525 | 1.0588871 | aut | 9 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 196 | EI0191 | CD037 | SI036 | 10.4761900 | % | NA | Figure 2 | 2005 | Sep | Sep | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 30.34071 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 29.67500 | 29.6750 | NA | 9 | 9 | 29.42034 | 29.525 | 1.0588871 | aut | 9 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 197 | EI0192 | CD037 | SI036 | 19.0476190 | % | NA | Figure 2 | 2005 | Oct | Oct | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 29.28740 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 28.43800 | 28.4380 | NA | 10 | 10 | 29.42034 | 29.525 | 1.0588871 | aut | 10 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 198 | EI0193 | CD037 | SI036 | 2.3809520 | % | NA | Figure 2 | 2005 | Nov | Nov | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 25.37511 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 26.46800 | 26.4680 | NA | 11 | 11 | 29.42034 | 29.525 | 1.0588871 | aut | 11 | fall | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7264404 | 302.82 | 5.594270 |
| 199 | EI0194 | CD037 | SI036 | 2.3809520 | % | NA | Figure 2 | 2006 | Mar | Mar | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | 22.66660 | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 24.15500 | 24.1550 | NA | 3 | 3 | 29.26933 | 29.395 | 0.7494438 | spr | 3 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8278503 | 302.82 | 5.594270 |
| 200 | EI0195 | CD037 | SI036 | 12.8571430 | % | NA | Figure 2 | 2006 | Apr | Apr | Figure 2 | Florida Keys, USA | Materials and Methods p2860 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.866528 | -80.67167 | 24.866528 | -80.67167 | Materials and Methods p2860, GoogleMaps | NA | Figure 2 | Black band; Prevalence extracted using MetaDigitise in Rstudio, n=10 | Atlantic Ocean | 25.32500 | 25.3250 | NA | 4 | 4 | 29.26933 | 29.395 | 0.7494438 | spr | 4 | spring | NA | 0.10 | NA | 0.16000 | 2 | Materials and Methods p2860 | 28 | 0 | NA | Quadrat | 10 | 4.0000 | 4.00 | 16.0000 | Materials and Methods p2860 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8278503 | 302.82 | 5.594270 |
| 201 | EI0196 | CD038 | SI037 | 6.9417476 | % | 2.330097 | Figure 3b | 2010 | Sep | Sep | Figure 3b | St Thomas Island, US Virgin Islands | Materials and Methods Study Site | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.344139 | -64.98239 | 18.344139 | -64.98239 | Materials and Methods Study Site, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=6 | Atlantic Ocean | 29.35800 | 29.3580 | NA | 9 | 9 | 29.16267 | 29.105 | 0.4016176 | aut | 9 | fall | 5.7075490 | NA | NA | 0.06000 | 1 | Materials and Methods Study site | NA | 0 | NA | Belt | 6 | 10.0000 | 1.00 | 10.0000 | Materials and Methods Field data collection methods, Figure 3b | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | VI-MRTL | 0.4828491 | 301.61 | 5.242833 |
| 202 | EI0197 | CD038 | SI037 | 1.2135922 | % | 1.262136 | Figure 3b | 2010 | Oct | Oct | Figure 3b | St Thomas Island, US Virgin Islands | Materials and Methods Study Site | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.344139 | -64.98239 | 18.344139 | -64.98239 | Materials and Methods Study Site, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Atlantic Ocean | 29.02000 | 29.0200 | NA | 10 | 10 | 29.16267 | 29.105 | 0.4016176 | aut | 10 | fall | 2.1860840 | NA | NA | 0.03000 | 1 | Materials and Methods Study site | NA | 0 | NA | Belt | 3 | 10.0000 | 1.00 | 10.0000 | Materials and Methods Field data collection methods, Figure 3b | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | VI-MRTL | 0.4828491 | 301.61 | 4.218555 |
| 203 | EI0198 | CD038 | SI037 | 4.1262136 | % | 2.378641 | Figure 3b | 2010 | Oct | Oct | Figure 3b | St Thomas Island, US Virgin Islands | Materials and Methods Study Site | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.344139 | -64.98239 | 18.344139 | -64.98239 | Materials and Methods Study Site, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Atlantic Ocean | 29.02000 | 29.0200 | NA | 10 | 10 | 29.16267 | 29.105 | 0.4016176 | aut | 10 | fall | 4.1199270 | NA | NA | 0.03000 | 1 | Materials and Methods Study site | NA | 0 | NA | Belt | 3 | 10.0000 | 1.00 | 10.0000 | Materials and Methods Field data collection methods, Figure 3b | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | VI-MRTL | 0.4828491 | 301.61 | 4.218555 |
| 204 | EI0199 | CD038 | SI037 | 1.6019417 | % | 1.747573 | Figure 3b | 2010 | Nov | Nov | Figure 3b | St Thomas Island, US Virgin Islands | Materials and Methods Study Site | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.344139 | -64.98239 | 18.344139 | -64.98239 | Materials and Methods Study Site, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=3 | Atlantic Ocean | 28.13800 | 28.1380 | NA | 11 | 11 | 29.16267 | 29.105 | 0.4016176 | aut | 11 | fall | 3.0268850 | NA | NA | 0.03000 | 1 | Materials and Methods Study site | NA | 0 | NA | Belt | 3 | 10.0000 | 1.00 | 10.0000 | Materials and Methods Field data collection methods, Figure 3b | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | VI-MRTL | 0.4828491 | 301.61 | 4.218555 |
| 205 | EI0200 | CD038 | SI037 | 0.0000000 | % | 0 | Figure 3b | 2011 | Feb | Feb | Figure 3b | St Thomas Island, US Virgin Islands | Materials and Methods Study Site | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.344139 | -64.98239 | 18.344139 | -64.98239 | Materials and Methods Study Site, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n=7 | Atlantic Ocean | 26.10800 | 26.1080 | NA | 2 | 2 | 28.73200 | 28.688 | 0.2370824 | win | 2 | winter | 0.0000000 | NA | NA | 0.07000 | 1 | Materials and Methods Study site | NA | 0 | NA | Belt | 7 | 10.0000 | 1.00 | 10.0000 | Materials and Methods Field data collection methods, Figure 3b | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | VI-MRTL | 0.4335632 | 301.61 | 4.218555 |
| 206 | EI0201 | CD039 | SI038 | 0.0000000 | % | 0 | Figure 4 | 2013 | Feb-Aug | Feb-Aug | Material and methods 2a Study site and species p2 | Lizard Island, GBR | Material and methods 2a Study site and species p2 | Western Pacific | Australia | -14.692154 | 145.45094 | -14.692154 | 145.45094 | Figure S1, GoogleMaps | NA | NA | Outside damselfish territory; n = 12 | Pacific Ocean | 26.58314 | 26.3850 | 2.0612886 | 2 | 8 | 28.76033 | 29.125 | 0.3214601 | multi | 8 | summer | NA | NA | NA | 0.06000 | 4 | Materials and methods 2d Coral disease surveys p3 | NA | 0 | NA | Belt-Quadrat | 60 | 1.0000 | 1.00 | 1.0000 | Materials and methods 2d Coral disease surveys p3 | Transect data is calculated based on quadrats (transect exists as a reference for where to place quadrats for collecting data); n for se is still 12 for number of transects (ignores that there are 5 quadrats per transect) | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6192932 | 301.73 | 0.000000 |
| 207 | EI0202 | CD039 | SI038 | 3.1700000 | % | 1.41 | Results 3c Coral disease surveys p5 | 2013 | Feb-Aug | Feb-Aug | Material and methods 2a Study site and species p2 | Lizard Island, GBR | Material and methods 2a Study site and species p2 | Western Pacific | Australia | -14.692154 | 145.45094 | -14.692154 | 145.45094 | Figure S1, GoogleMaps | NA | NA | Inside damselfish territory; n = 12 | Pacific Ocean | 26.58314 | 26.3850 | 2.0612886 | 2 | 8 | 28.76033 | 29.125 | 0.3214601 | multi | 8 | summer | NA | NA | NA | 0.06000 | 4 | Materials and methods 2d Coral disease surveys p3 | NA | 0 | NA | Belt-Quadrat | 60 | 1.0000 | 1.00 | 1.0000 | Materials and methods 2d Coral disease surveys p3 | Transect data is calculated based on quadrats (transect exists as a reference for where to place quadrats for collecting data); n for se is still 12 for number of transects (ignores that there are 5 quadrats per transect) | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6192932 | 301.73 | 0.000000 |
| 208 | EI0203 | CD040 | SI039 | 0.1090909 | % | 9.09E-02 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Bird Islet, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 209 | EI0204 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Lizard Head, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 210 | EI0205 | CD040 | SI039 | 0.1272727 | % | 0.10909091 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | North Reef, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 211 | EI0206 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | South Island, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 212 | EI0207 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Washing Machine, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 213 | EI0208 | CD040 | SI039 | 2.3272727 | % | 1.52727273 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Channel, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 214 | EI0209 | CD040 | SI039 | 3.4181818 | % | 0.21818182 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Ghost Beach, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 215 | EI0210 | CD040 | SI039 | 0.4181818 | % | 0.21818182 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Loomis Reef, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 216 | EI0211 | CD040 | SI039 | 0.6545455 | % | 0.30909091 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Loomis Beach, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | NA | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 217 | EI0212 | CD040 | SI039 | 3.4181818 | % | 1.8 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Palfrey, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 218 | EI0213 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Casuarina, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 219 | EI0214 | CD040 | SI039 | 1.7818182 | % | 0.89090909 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Horseshoe, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 220 | EI0215 | CD040 | SI039 | 0.3272727 | % | 0.18181818 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Little Vickys, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 221 | EI0216 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Mushroom, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 222 | EI0217 | CD040 | SI039 | 0.1818182 | % | 0.14545455 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Vickies, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Brown band disease; Prevalence extracted using MetaDigitise in R, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | NA | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 223 | EI0218 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Bird Islet, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 224 | EI0219 | CD040 | SI039 | 0.1997439 | % | 0.1649168 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Lizard Head, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.2856442 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 225 | EI0220 | CD040 | SI039 | 0.2563380 | % | 0.1177977 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | North Reef, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.2040316 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 226 | EI0221 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | South Island, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 227 | EI0222 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Washing Machine, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 228 | EI0223 | CD040 | SI039 | 0.7157490 | % | 0.6714469 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Channel, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 1.1629801 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 229 | EI0224 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Ghost Beach, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 230 | EI0225 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Loomis Reef, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 231 | EI0226 | CD040 | SI039 | 0.5154930 | % | 0.2473752 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Loomis Beach, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.4284663 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 232 | EI0227 | CD040 | SI039 | 1.7288092 | % | 1.6727273 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Palfrey, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 2.8972486 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 233 | EI0228 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Casuarina, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 234 | EI0229 | CD040 | SI039 | 1.5638924 | % | 0.7892446 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Horseshoe, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 1.3670117 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 235 | EI0230 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Little Vickys, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 236 | EI0231 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Mushroom, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 237 | EI0232 | CD040 | SI039 | 0.0000000 | % | 0 | Figure 3a | 2009 | Dec-Feb | Dec-Feb | Materials and methods Study site and sampling design | Vickies, Lizard Island, GBR | Figure 3a, Materials and methods Study site and sampling design | Western Pacific | Australia | -14.666670 | 145.45000 | -14.666670 | 145.45000 | Materials and methods Study site and sampling design, GoogleMaps | NA | NA | Black band disease; Prevalence extracted using MetaDigitise in Rstudio, n=3 | Pacific Ocean | 28.78367 | 28.6180 | 0.3474996 | 12 | 2 | 28.78367 | 28.618 | 0.3474996 | aut | 6 | summer | 0.0000000 | NA | NA | 0.12000 | 1 | Figure 3a | NA | 1 | Effect sizes are per site | Belt | 3 | 20.0000 | 2.00 | 40.0000 | Materials and methods Study site and sampling design p474 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3457031 | 301.74 | 1.044272 |
| 238 | EI0233 | CD041 | SI040 | 2.7000000 | % | NA | Figure 3a | 1999 | Jun | Jun | Methods p668 | Little Cayman | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.684933 | -80.07788 | 19.684933 | -80.07788 | Table 1 Mixing Bowl, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 73 | Atlantic Ocean | 28.68500 | 28.6850 | NA | 6 | 6 | 29.18267 | 29.028 | 0.5903948 | sum | 6 | summer | NA | NA | NA | 0.73000 | 5 | Table 1 | 821 | 1 | NA | Line | 73 | 10.0000 | 1.00 | 10.0000 | Methods p668 | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Figure 3b | 0.7939529 | 302.61 | 3.505726 |
| 239 | EI0234 | CD041 | SI040 | 6.0000000 | % | NA | Figure 3a | 2002 | Jul-Aug | Jul-Aug | Methods p668 | Little Cayman | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.684933 | -80.07788 | 19.684933 | -80.07788 | Table 1 Mixing Bowl, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 41 | Atlantic Ocean | 29.68150 | 29.6815 | 0.5069949 | 7 | 8 | 29.33367 | 29.323 | 0.7010611 | sum | 7 | summer | NA | NA | NA | 0.41000 | 4 | Table 1 | 516 | 1 | NA | Line | 41 | 10.0000 | 1.00 | 10.0000 | Methods p668 | NA | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Figure 3b | 0.3357086 | 302.61 | 0.000000 |
| 240 | EI0235 | CD041 | SI040 | 4.6000000 | % | NA | Figure 3a | 2003 | Jul-Aug | Jul-Aug | Methods p668 | Little Cayman | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.684933 | -80.07788 | 19.684933 | -80.07788 | Table 1 Mixing Bowl, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 36 | Atlantic Ocean | 29.34400 | 29.3440 | 0.3549668 | 7 | 8 | 29.18867 | 29.093 | 0.3679483 | sum | 7 | summer | NA | NA | NA | 0.36000 | 4 | Table 1 | 501 | 1 | NA | Line | 36 | 10.0000 | 1.00 | 10.0000 | Methods p668 | NA | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Figure 3b | 0.4328613 | 302.61 | 0.000000 |
| 241 | EI0236 | CD041 | SI040 | 6.7500000 | % | NA | Figure 3a | 2004 | Jul-Aug | Jul-Aug | Methods p668 | Little Cayman | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.684933 | -80.07788 | 19.684933 | -80.07788 | Table 1 Mixing Bowl, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 88 | Atlantic Ocean | 29.49900 | 29.4990 | 0.2955715 | 7 | 8 | 29.21867 | 29.290 | 0.5286226 | sum | 7 | summer | NA | NA | NA | 0.88000 | 9 | Table 1 | 1125 | 1 | NA | Line | 88 | 10.0000 | 1.00 | 10.0000 | Methods p668 | NA | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Figure 3b | 0.6993103 | 302.61 | 0.000000 |
| 242 | EI0237 | CD042 | SI041 | 0.0200000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Shallow sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0400000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 243 | EI0238 | CD042 | SI041 | 0.0200000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Shallow sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0400000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 244 | EI0239 | CD042 | SI041 | 0.3200000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Shallow sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.3000000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 245 | EI0240 | CD042 | SI041 | 2.9700000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Shallow sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 1.7000000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 246 | EI0241 | CD042 | SI041 | 0.0000000 | % | 0 | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Shallow sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0000000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “Yellow Blotch” in paper marked as ywllow band | 0.5457077 | 301.14 | 8.795700 |
| 247 | EI0242 | CD042 | SI041 | 0.0200000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Deep sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0400000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 248 | EI0243 | CD042 | SI041 | 0.0200000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Deep sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0400000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 249 | EI0244 | CD042 | SI041 | 0.0000000 | % | 0 | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Deep sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0000000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 250 | EI0245 | CD042 | SI041 | 5.0300000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Deep sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 1.9500000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5457077 | 301.14 | 8.795700 |
| 251 | EI0246 | CD042 | SI041 | 0.0700000 | % | NA | Table 3 | 2000 | Aug | Aug | Materials and Methods p40 | Madrizqui Key, Los Roques Archipelago | Materials and Methods p40 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.936455 | -66.67740 | 11.936455 | -66.67740 | Materials and Methods p40, GoogleMaps | NA | NA | Deep sites relative percent of diseased colonies | Atlantic Ocean | 27.75000 | 27.7500 | NA | 8 | 8 | 27.08034 | 26.878 | 0.5948922 | sum | 8 | summer | 0.0700000 | NA | NA | 0.60000 | 2 | Materials and Methods p40 | 1439 | 1 | NA | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p40 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “Yellow Blotch” in paper marked as ywllow band | 0.5457077 | 301.14 | 8.795700 |
| 256 | EI0251 | CD009 | SI043 | 28.6000000 | % | NA | Results p36 | 2002 | Jun-Aug | Jun-Aug | Materials and methods Study site p35 | Akumal Bay, Quintana Roo, Mexican Caribbean | Materials and methods Study site p34 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 20.391256 | -87.31472 | 20.391256 | -87.31472 | GoogleMaps Akumal Bay | 29.73000 | Table 1 | 18.4–41.5% 95% CI | Atlantic Ocean | 29.11933 | 29.0730 | 0.3895717 | 6 | 8 | 29.11933 | 29.073 | 0.3895717 | sum | 6 | summer | NA | NA | 0.9333 | 1.44000 | 1 | Figure 1 | NA | 0 | NA | Belt | 4 | 60.0000 | 6.00 | 360.0000 | Materials and methods Sampling and study design p35 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1728516 | 301.86 | 0.000000 |
| 257 | EI0252 | CD011 | SI044 | 5.0862070 | % | 2.465517 | Figure 2 | 2007 | Jan | Jan | p293 | Pedra de Leste, Abrolhos Bank, eastern Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -17.959660 | -38.70108 | -17.959660 | -38.70108 | GoogleMaps Abrolhos Marine National Park | 27.40000 | p293 | Prevalence extracted using MetaDigitise in Rstudio, n = 4; This region is not recognized in Hoegh-Guldberg map | Atlantic Ocean | 27.23300 | 27.2330 | NA | 1 | 1 | 26.98500 | 27.005 | 0.5352811 | sum | 7 | summer | 4.9310340 | NA | NA | 0.04000 | 1 | p293 | NA | 0 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | p293 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “White plague-like disease” categorized as white syndrome | 0.6721191 | 300.09 | 0.000000 |
| 258 | EI0253 | CD011 | SI044 | 3.3620690 | % | 1.931034 | Figure 2 | 2007 | Jul | Jul | p293 | Pedra de Leste, Abrolhos Bank, eastern Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -17.959660 | -38.70108 | -17.959660 | -38.70108 | GoogleMaps Abrolhos Marine National Park | 27.40000 | p293 | Prevalence extracted using MetaDigitise in Rstudio, n = 4; This region is not recognized in Hoegh-Guldberg map | Atlantic Ocean | 25.25800 | 25.2580 | NA | 7 | 7 | 26.98500 | 27.005 | 0.5352811 | win | 1 | winter | 3.8620690 | NA | NA | 0.04000 | 1 | p293 | NA | 0 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | p293 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “White plague-like disease” categorized as white syndrome | 0.1371307 | 300.09 | 0.000000 |
| 259 | EI0254 | CD011 | SI044 | 7.4137930 | % | 2.465517 | Figure 2 | 2007 | Jan | Jan | p293 | Timbebas, Abrolhos Bank, eastern Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -17.959660 | -38.70108 | -17.959660 | -38.70108 | GoogleMaps Abrolhos Marine National Park | 27.40000 | p293 | Prevalence extracted using MetaDigitise in Rstudio, n = 4; This region is not recognized in Hoegh-Guldberg map | Atlantic Ocean | 27.23300 | 27.2330 | NA | 1 | 1 | 26.98500 | 27.005 | 0.5352811 | sum | 7 | summer | 4.9310340 | NA | NA | 0.04000 | 1 | p293 | NA | 0 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | p293 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “White plague-like disease” categorized as white syndrome | 0.6721191 | 300.09 | 0.000000 |
| 260 | EI0255 | CD011 | SI044 | 1.3275860 | % | 1.068966 | Figure 2 | 2007 | Jul | Jul | p293 | Timbebas, Abrolhos Bank, eastern Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -17.959660 | -38.70108 | -17.959660 | -38.70108 | GoogleMaps Abrolhos Marine National Park | 27.40000 | p293 | Prevalence extracted using MetaDigitise in Rstudio, n = 4; This region is not recognized in Hoegh-Guldberg map | Atlantic Ocean | 25.25800 | 25.2580 | NA | 7 | 7 | 26.98500 | 27.005 | 0.5352811 | win | 1 | winter | 2.1379310 | NA | NA | 0.04000 | 1 | p293 | NA | 0 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | p293 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “White plague-like disease” categorized as white syndrome | 0.1371307 | 300.09 | 0.000000 |
| 261 | EI0256 | CD015 | SI045 | 38.4920600 | % | NA | Figure 5 | 2010 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.50290 | 29.1575 | 3.1298983 | 2 | 11 | 29.43000 | 29.310 | 0.4960097 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.0906982 | 302.58 | 0.000000 |
| 262 | EI0257 | CD015 | SI045 | 41.6666700 | % | NA | Figure 5 | 2011 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.91100 | 28.7740 | 2.5221626 | 2 | 11 | 29.19867 | 29.343 | 0.9299391 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.2971497 | 302.58 | 0.000000 |
| 263 | EI0258 | CD015 | SI045 | 53.1746000 | % | NA | Figure 5 | 2012 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.87460 | 28.3880 | 2.1884169 | 2 | 11 | 28.78800 | 29.063 | 0.9672772 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.4746475 | 302.58 | 2.218572 |
| 264 | EI0259 | CD015 | SI045 | 20.6349200 | % | NA | Figure 5 | 2013 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.74260 | 27.9090 | 2.2387222 | 2 | 11 | 28.32433 | 28.273 | 0.8062260 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.5521393 | 302.58 | 0.000000 |
| 265 | EI0260 | CD015 | SI045 | 51.9841300 | % | NA | Figure 5 | 2014 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 27.18530 | 28.7290 | 2.1712860 | 2 | 11 | 29.15867 | 29.498 | 1.0701410 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.6310654 | 302.58 | 0.000000 |
| 266 | EI0261 | CD015 | SI045 | 53.5714300 | % | NA | Figure 5 | 2015 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 27.63430 | 29.2255 | 1.9786979 | 2 | 11 | 29.43200 | 29.488 | 0.4436586 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.7693024 | 302.58 | 2.238561 |
| 267 | EI0262 | CD015 | SI045 | 39.6825400 | % | NA | Figure 5 | 2016 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | BCA Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 64; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 27.31800 | 29.3500 | 2.4052447 | 2 | 11 | 29.55100 | 30.095 | 0.8223307 | multi | 2 | winter | NA | NA | NA | 0.44800 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 64 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.5317917 | 302.58 | 0.000000 |
| 268 | EI0263 | CD015 | SI045 | 78.9682500 | % | NA | Figure 6 | 2010 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.50290 | 29.1575 | 3.1298983 | 2 | 11 | 29.43000 | 29.310 | 0.4960097 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.0906982 | 302.58 | 0.000000 |
| 269 | EI0264 | CD015 | SI045 | 62.3015900 | % | NA | Figure 6 | 2011 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.91100 | 28.7740 | 2.5221626 | 2 | 11 | 29.19867 | 29.343 | 0.9299391 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.2971497 | 302.58 | 0.000000 |
| 270 | EI0265 | CD015 | SI045 | 68.6507900 | % | NA | Figure 6 | 2012 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.87460 | 28.3880 | 2.1884169 | 2 | 11 | 28.78800 | 29.063 | 0.9672772 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.4746475 | 302.58 | 2.218572 |
| 271 | EI0266 | CD015 | SI045 | 39.6825400 | % | NA | Figure 6 | 2013 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 26.74260 | 27.9090 | 2.2387222 | 2 | 11 | 28.32433 | 28.273 | 0.8062260 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.5521393 | 302.58 | 0.000000 |
| 272 | EI0267 | CD015 | SI045 | 55.9523800 | % | NA | Figure 6 | 2014 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 27.18530 | 28.7290 | 2.1712860 | 2 | 11 | 29.15867 | 29.498 | 1.0701410 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.6310654 | 302.58 | 0.000000 |
| 273 | EI0268 | CD015 | SI045 | 73.0158700 | % | NA | Figure 6 | 2015 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 27.63430 | 29.2255 | 1.9786979 | 2 | 11 | 29.43200 | 29.488 | 0.4436586 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.7693024 | 302.58 | 2.238561 |
| 274 | EI0269 | CD015 | SI045 | 72.2222200 | % | NA | Figure 6 | 2016 | Feb-Mar, Jun-Aug, Oct-Nov | Feb-Mar, Jun-Aug, Oct-Nov | Materials and Methods | Scooter Patch, Southeast Florida | Materials and Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.166320 | -80.04526 | 26.166320 | -80.04526 | GoogleMaps Broward County, FL | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 62; paper includes SE in written material for some measurements, but not in graphs | Atlantic Ocean | 27.31800 | 29.3500 | 2.4052447 | 2 | 11 | 29.55100 | 30.095 | 0.8223307 | multi | 2 | winter | NA | NA | NA | 0.43400 | 1 | Materials and Methods | NA | 0 | Effect sizes are per site | Line | 62 | 7.0000 | 1.00 | 7.0000 | Materials and Methods | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Pooled in paper as “white disease” | 0.5317917 | 302.58 | 0.000000 |
| 275 | EI0284 | CD020 | SI046 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Marker 32, Yanbu, Red Sea | Table 1 | Western Indian Ocean | Middle East | 23.866400 | 37.89130 | 23.866400 | 37.89130 | Table 1 | NA | NA | NA | Indian Ocean | 29.23050 | 29.2305 | 1.2692567 | 10 | 11 | 29.58367 | 29.770 | 1.5011987 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 726 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7028351 | 303.04 | 0.000000 |
| 276 | EI0285 | CD020 | SI047 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Marker 35, Yanbu, Red Sea | Table 1 | Western Indian Ocean | Middle East | 23.820700 | 37.93500 | 23.820700 | 37.93500 | Table 1 | NA | NA | NA | Indian Ocean | 29.23050 | 29.2305 | 1.2692567 | 10 | 11 | 29.58367 | 29.770 | 1.5011987 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 930 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7257004 | 303.08 | 0.000000 |
| 277 | EI0286 | CD020 | SI048 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Abu Galaba, Yanbu, Red Sea | Table 1 | Western Indian Ocean | Middle East | 23.789100 | 37.93930 | 23.789100 | 37.93930 | Table 1 | NA | NA | NA | Indian Ocean | 29.23050 | 29.2305 | 1.2692567 | 10 | 11 | 29.58367 | 29.770 | 1.5011987 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 848 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7285690 | 303.15 | 0.000000 |
| 278 | EI0287 | CD020 | SI049 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Fringing reef 1, Yanbu, Red Sea | Table 1 | Western Indian Ocean | Middle East | 24.136200 | 37.93960 | 24.136200 | 37.93960 | Table 1 | NA | NA | NA | Indian Ocean | 29.01400 | 29.0140 | 1.2883489 | 10 | 11 | 29.52700 | 29.683 | 1.4572761 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 1308 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 3.3060608 | 302.80 | 1.300007 |
| 279 | EI0288 | CD020 | SI050 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Marker 10, Yanbu, Red Sea | Table 1 | Western Indian Ocean | Middle East | 24.018900 | 37.96660 | 24.018900 | 37.96660 | Table 1 | NA | NA | NA | Indian Ocean | 29.01400 | 29.0140 | 1.2883489 | 10 | 11 | 29.52700 | 29.683 | 1.4572761 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 1749 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.9114532 | 302.86 | 1.298570 |
| 280 | EI0289 | CD020 | SI051 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Fringing reef 2, Yanbu, Red Sea | Table 1 | Western Indian Ocean | Middle East | 24.145200 | 37.91490 | 24.145200 | 37.91490 | Table 1 | NA | NA | NA | Indian Ocean | 29.01400 | 29.0140 | 1.2883489 | 10 | 11 | 29.52700 | 29.683 | 1.4572761 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 1830 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 3.3060608 | 302.80 | 1.300007 |
| 281 | EI0290 | CD020 | SI052 | 0.0500000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Abu Madafi, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.076600 | 38.77510 | 22.076600 | 38.77510 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 2184 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9992828 | 303.88 | 0.000000 |
| 282 | EI0291 | CD020 | SI053 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Al Fahal, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.111900 | 38.84110 | 22.111900 | 38.84110 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 6000 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9107361 | 303.89 | 0.000000 |
| 283 | EI0292 | CD020 | SI054 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Al-Mashpah, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.077200 | 38.77440 | 22.077200 | 38.77440 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 4200 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9992828 | 303.88 | 0.000000 |
| 284 | EI0293 | CD020 | SI055 | 0.0100000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Inner Fsar, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.235800 | 39.03040 | 22.235800 | 39.03040 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 6852 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7371521 | 303.90 | 0.000000 |
| 285 | EI0294 | CD020 | SI056 | 0.0200000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Shaab, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.201200 | 38.99920 | 22.201200 | 38.99920 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 5778 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7471619 | 303.91 | 0.000000 |
| 286 | EI0295 | CD020 | SI057 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Shi’b Nazar, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.340900 | 38.85210 | 22.340900 | 38.85210 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 3294 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2971344 | 303.92 | 0.000000 |
| 287 | EI0296 | CD020 | SI058 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Tahlah, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.275000 | 39.04970 | 22.275000 | 39.04970 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 3780 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7753372 | 303.90 | 0.000000 |
| 288 | EI0297 | CD020 | SI059 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Qita al Kirsh, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.425700 | 38.99570 | 22.425700 | 38.99570 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 5748 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8378448 | 303.88 | 0.000000 |
| 289 | EI0298 | CD020 | SI060 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Um Alkthal, Thuwal, Red Sea | Table 1 | Western Indian Ocean | Middle East | 22.165300 | 38.93910 | 22.165300 | 38.93910 | Table 1 | NA | NA | NA | Indian Ocean | 29.84050 | 29.8405 | 1.1702622 | 10 | 11 | 29.81200 | 29.983 | 1.4262102 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 5208 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7585526 | 303.90 | 0.000000 |
| 290 | EI0299 | CD020 | SI061 | 0.2100000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | La Plage, Jeddah, Red Sea | Table 1 | Western Indian Ocean | Middle East | 21.709200 | 39.08320 | 21.707160 | 38.80293 | Table 1 | NA | NA | coordinates not found in SST dataset - reselected from nearby coordinates on GoogleMaps | Indian Ocean | 30.21750 | 30.2175 | 1.0500527 | 10 | 11 | 30.01467 | 30.148 | 1.3499478 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 474 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9700012 | 303.87 | 0.000000 |
| 291 | EI0300 | CD020 | SI062 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Abu Lath, Al-Lith, Red Sea | Table 1 | Western Indian Ocean | Middle East | 19.955400 | 40.15430 | 19.955400 | 40.15430 | Table 1 | NA | NA | NA | Indian Ocean | 31.33050 | 31.3305 | 0.7318554 | 10 | 11 | 30.54600 | 30.505 | 0.6394867 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 5556 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1789246 | 304.32 | 3.622857 |
| 292 | EI0301 | CD020 | SI063 | 0.0300000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | South Reef, Al-Lith, Red Sea | Table 1 | Western Indian Ocean | Middle East | 19.899850 | 40.15140 | 19.899850 | 40.15140 | Table 1 | NA | NA | NA | Indian Ocean | 31.33050 | 31.3305 | 0.7318554 | 10 | 11 | 30.54600 | 30.505 | 0.6394867 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 3720 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1382217 | 304.35 | 1.017127 |
| 293 | EI0302 | CD020 | SI064 | 0.0000000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Al-Lith 3, Al-Lith, Red Sea | Table 1 | Western Indian Ocean | Middle East | 19.860800 | 40.22820 | 19.860800 | 40.22820 | Table 1 | NA | NA | NA | Indian Ocean | 31.33050 | 31.3305 | 0.7318554 | 10 | 11 | 30.54600 | 30.505 | 0.6394867 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 4320 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3139267 | 304.36 | 1.071428 |
| 294 | EI0303 | CD020 | SI065 | 0.0200000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Qita Al Kirsh, Al-Lith, Red Sea | Table 1 | Western Indian Ocean | Middle East | 20.140700 | 40.09310 | 20.140700 | 40.09310 | Table 1 | NA | NA | NA | Indian Ocean | 30.81250 | 30.8125 | 0.8379212 | 10 | 11 | 30.25667 | 30.300 | 1.0156939 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 6588 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4396286 | 304.25 | 4.065706 |
| 295 | EI0304 | CD020 | SI066 | 1.7200000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Fringing reef 1, Al-Lith, Red Sea | Table 1 | Western Indian Ocean | Middle East | 20.173200 | 40.16130 | 20.173200 | 40.16130 | Table 1 | NA | NA | NA | Indian Ocean | 30.81250 | 30.8125 | 0.8379212 | 10 | 11 | 30.25667 | 30.300 | 1.0156939 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 1281 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.0107117 | 304.25 | 4.219973 |
| 296 | EI0305 | CD020 | SI067 | 0.1200000 | % | NA | Table 1 | 2015 | Oct-Nov | Oct-Nov | Materials and Methods Black band disease surveys | Whaleshark reef, Al-Lith, Red Sea | Table 1 | Western Indian Ocean | Middle East | 20.123000 | 40.21180 | 20.123000 | 40.21180 | Table 1 | NA | NA | NA | Indian Ocean | 30.81250 | 30.8125 | 0.8379212 | 10 | 11 | 30.25667 | 30.300 | 1.0156939 | aut | 10 | fall | NA | NA | NA | 0.15000 | 22 | Material and Methods Black band disease surveys | 1716 | 1 | NA | Belt | 1 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Black band disease surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.9178772 | 304.26 | 4.367127 |
| 297 | EI0306 | CD016 | SI068 | 3.2200000 | % | 0.8 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Borendi, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.786667 | 166.46500 | -21.786667 | 166.46500 | Materials and Methods Study locations p166 | NA | NA | pigmentation | Pacific Ocean | 27.09000 | 27.0900 | NA | 3 | 3 | 26.86433 | 27.055 | 0.5132851 | aut | 9 | fall | NA | NA | NA | 0.06000 | 4 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3939285 | 300.54 | 0.000000 |
| 298 | EI0307 | CD016 | SI068 | 1.5200000 | % | 0.44 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Borendi, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.786667 | 166.46500 | -21.786667 | 166.46500 | Materials and Methods Study locations p166 | NA | NA | growth anomoly | Pacific Ocean | 27.09000 | 27.0900 | NA | 3 | 3 | 26.86433 | 27.055 | 0.5132851 | aut | 9 | fall | NA | NA | NA | 0.06000 | 4 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3939285 | 300.54 | 0.000000 |
| 299 | EI0308 | CD016 | SI068 | 1.0700000 | % | 0.47 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Borendi, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.786667 | 166.46500 | -21.786667 | 166.46500 | Materials and Methods Study locations p166 | NA | NA | white syndrome | Pacific Ocean | 27.09000 | 27.0900 | NA | 3 | 3 | 26.86433 | 27.055 | 0.5132851 | aut | 9 | fall | NA | NA | NA | 0.06000 | 4 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3939285 | 300.54 | 0.000000 |
| 300 | EI0309 | CD016 | SI069 | 11.1000000 | % | 2.7 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Kaala, New Caledonia | Table 1 | Western Pacific | Melanesia | -20.615000 | 164.31500 | -20.615000 | 164.31500 | Materials and Methods Study locations p166 | NA | NA | pigmentation | Pacific Ocean | 27.29300 | 27.2930 | NA | 3 | 3 | 27.29333 | 27.565 | 0.5100074 | aut | 9 | fall | NA | NA | NA | 0.06000 | 3 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3778381 | 300.75 | 0.000000 |
| 301 | EI0310 | CD016 | SI069 | 3.0100000 | % | 1.03 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Kaala, New Caledonia | Table 1 | Western Pacific | Melanesia | -20.615000 | 164.31500 | -20.615000 | 164.31500 | Materials and Methods Study locations p166 | NA | NA | growth anomoly | Pacific Ocean | 27.29300 | 27.2930 | NA | 3 | 3 | 27.29333 | 27.565 | 0.5100074 | aut | 9 | fall | NA | NA | NA | 0.06000 | 3 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3778381 | 300.75 | 0.000000 |
| 302 | EI0311 | CD016 | SI069 | 0.0000000 | % | 0 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Kaala, New Caledonia | Table 1 | Western Pacific | Melanesia | -20.615000 | 164.31500 | -20.615000 | 164.31500 | Materials and Methods Study locations p166 | NA | NA | white syndrome | Pacific Ocean | 27.29300 | 27.2930 | NA | 3 | 3 | 27.29333 | 27.565 | 0.5100074 | aut | 9 | fall | NA | NA | NA | 0.06000 | 3 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3778381 | 300.75 | 0.000000 |
| 303 | EI0312 | CD016 | SI070 | 0.3100000 | % | 0.31 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Nepoui, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.343333 | 164.99500 | -21.343300 | 164.91940 | Materials and Methods Study locations p166 | NA | NA | coordinates not found in SST dataset - reselected from a nearby coordinate in GoogleMaps | Pacific Ocean | 26.85500 | 26.8550 | NA | 3 | 3 | 26.80767 | 27.035 | 0.5457484 | aut | 9 | fall | NA | NA | NA | 0.06000 | 2 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5389175 | 300.34 | 0.000000 |
| 304 | EI0313 | CD016 | SI070 | 4.1600000 | % | 2.54 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Nepoui, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.343333 | 164.99500 | -21.343300 | 164.91940 | Materials and Methods Study locations p166 | NA | NA | coordinates not found in SST dataset - reselected from a nearby coordinate in GoogleMaps | Pacific Ocean | 26.85500 | 26.8550 | NA | 3 | 3 | 26.80767 | 27.035 | 0.5457484 | aut | 9 | fall | NA | NA | NA | 0.06000 | 2 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5389175 | 300.34 | 0.000000 |
| 305 | EI0314 | CD016 | SI070 | 0.0000000 | % | 0 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Nepoui, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.343333 | 164.99500 | -21.343300 | 164.91940 | Materials and Methods Study locations p166 | NA | NA | coordinates not found in SST dataset - reselected from a nearby coordinate in GoogleMaps | Pacific Ocean | 26.85500 | 26.8550 | NA | 3 | 3 | 26.80767 | 27.035 | 0.5457484 | aut | 9 | fall | NA | NA | NA | 0.06000 | 2 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5389175 | 300.34 | 0.000000 |
| 306 | EI0315 | CD016 | SI071 | 2.0700000 | % | 0.47 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Thio, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.616667 | 166.25500 | -21.616667 | 166.25500 | Materials and Methods Study locations p166 | NA | NA | pigmentation | Pacific Ocean | 27.09000 | 27.0900 | NA | 3 | 3 | 26.86433 | 27.055 | 0.5132851 | aut | 9 | fall | NA | NA | NA | 0.06000 | 3 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3728485 | 300.62 | 0.000000 |
| 307 | EI0316 | CD016 | SI071 | 1.7800000 | % | 0.6 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Thio, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.616667 | 166.25500 | -21.616667 | 166.25500 | Materials and Methods Study locations p166 | NA | NA | growth anomoly | Pacific Ocean | 27.09000 | 27.0900 | NA | 3 | 3 | 26.86433 | 27.055 | 0.5132851 | aut | 9 | fall | NA | NA | NA | 0.06000 | 3 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3728485 | 300.62 | 0.000000 |
| 308 | EI0317 | CD016 | SI071 | 0.0700000 | % | 7.00E-02 | Table 1 | 2013 | Mar | Mar | Materials and Methods Study locations p166 | Thio, New Caledonia | Table 1 | Western Pacific | Melanesia | -21.616667 | 166.25500 | -21.616667 | 166.25500 | Materials and Methods Study locations p166 | NA | NA | white syndrome | Pacific Ocean | 27.09000 | 27.0900 | NA | 3 | 3 | 26.86433 | 27.055 | 0.5132851 | aut | 9 | fall | NA | NA | NA | 0.06000 | 3 | Materials and Methods Survey methods p167 | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Materials and Methods Survey method p167 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3728485 | 300.62 | 0.000000 |
| 309 | EI0318 | CD046 | SI072 | 0.0000000 | % | 0 | Discussion | 2018 | Feb-Mar | Feb-Mar | Materials and Methods Data collection and construction of ortho-mosaics | Cozumel Reefs National Park | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 20.385380 | -87.02705 | 20.385380 | -87.02705 | GoogleMaps Cozumel Reef National Park, Figure 1 | NA | NA | NA | Atlantic Ocean | 26.77250 | 26.7725 | 0.1590993 | 2 | 3 | 29.06467 | 29.203 | 0.4343486 | spr | 2 | winter | 0.0000000 | NA | NA | 2.70000 | 6 | Figure 1 | NA | 1 | Sampling area calculated from transect data, but summing sampling area reported in Table 2 = 3.775 | Belt | 3 | 30.0000 | 5.00 | 150.0000 | Materials and Methods Data collection and construction of ortho-mosaics | NA | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6324921 | 301.91 | 6.024253 |
| 310 | EI0319 | CD047 | SI073 | 13.0000000 | % | 5.5 | Results Island patterns p5 | 2008 | Feb-Apr | Feb-Apr | Materials and Methods Survey design p3 | Christmas Island | Results Island patterns p5 | Eastern Indian Ocean | Southeast Asia | -10.500000 | 105.66670 | -10.500000 | 105.66670 | Materials and Methods Study site p2, GoogleMaps | NA | NA | NA | Indian Ocean | 28.86633 | 28.8580 | 0.2026289 | 2 | 4 | 28.50434 | 28.798 | 0.3159690 | aut | 8 | summer | NA | NA | NA | 4.50000 | 10 | Materials and Methods Survey design p3 | NA | 1 | Acropora plate corals | Belt | 3 | 30.0000 | 5.00 | 150.0000 | Materials and Methods Survey design p3 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1864319 | 301.97 | 0.000000 |
| 311 | EI0320 | CD047 | SI074 | 0.8500000 | % | 0.63 | Results Island patterns p5 | 2008 | Feb-Apr | Feb-Apr | Materials and Methods Survey design p3 | Cocos Islands | Results Island patterns p5 | Eastern Indian Ocean | Southeast Asia | -12.200000 | 96.90000 | -12.200000 | 96.90000 | Materials and Methods Study site p2, GoogleMaps | NA | NA | NA | Indian Ocean | 28.51700 | 28.5230 | 0.0103921 | 2 | 4 | 27.58933 | 27.755 | 0.6544199 | aut | 8 | summer | NA | NA | NA | 4.05000 | 9 | Materials and Methods Survey design p3 | NA | 1 | Acropora plate corals | Belt | 3 | 30.0000 | 5.00 | 150.0000 | Materials and Methods Survey design p3 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 301.49 | 0.000000 |
| 312 | EI0321 | CD048 | SI075 | 71.0000000 | % | NA | Table 3 | 2015 | Mar | Mar | Materials and Methods Underwater survey p80 | Malvan Marine Sanctuary | Figure 1 | Western Indian Ocean | Central Indian | 16.044722 | 73.46139 | 16.044722 | 73.46139 | Table 3, GoogleMaps | NA | NA | Site 1 | Indian Ocean | 28.22300 | 28.2230 | NA | 3 | 3 | 29.07267 | 28.993 | 0.5369502 | spr | 3 | spring | NA | NA | NA | 0.30000 | 1 | Figure 1 | 24 | 0 | Effect sizes are per site, colony number mean per transect | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods Underwater survey p81 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8071289 | 302.54 | 0.000000 |
| 313 | EI0322 | CD048 | SI076 | 40.0000000 | % | NA | Table 3 | 2015 | Mar | Mar | Materials and Methods Underwater survey p80 | Malvan Marine Sanctuary | Figure 1 | Western Indian Ocean | Central Indian | 16.065000 | 73.45722 | 16.065000 | 73.45722 | Table 3, GoogleMaps | NA | NA | Site 2 | Indian Ocean | 28.22300 | 28.2230 | NA | 3 | 3 | 29.07267 | 28.993 | 0.5369502 | spr | 3 | spring | NA | NA | NA | 0.30000 | 1 | Figure 1 | 10 | 0 | Effect sizes are per site, colony number mean per transect | Belt | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods Underwater survey p81 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7456970 | 302.53 | 0.000000 |
| 314 | EI0323 | CD049 | SI077 | 2.5405410 | % | 0.4504505 | Figure 4b | 2005 | Aug-Sep | Aug-Sep | Materials and Methods | Kingman, Line Islands | Figure 1 | Western Pacific | Micronesia | 6.410630 | -162.42692 | 6.410630 | -162.42692 | GoogleMaps Kingman Reef | 27.90000 | Table 1 | Prevalence extracted using MetaDigitise in Rstudio, n = 20 | Pacific Ocean | 28.88150 | 28.8815 | 0.1322292 | 8 | 9 | 28.54300 | 28.488 | 0.2226552 | aut | 8 | summer | 2.0144760 | NA | 0.7000 | 0.80000 | 10 | Materials and Methods Coral Disease | NA | 1 | NA | Belt | 2 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Coral Disease | NA | 5 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2214203 | 302.13 | 0.000000 |
| 315 | EI0324 | CD049 | SI078 | 4.8288290 | % | 2 | Figure 4b | 2005 | Aug-Sep | Aug-Sep | Materials and Methods | Palmyra, Line Islands | Figure 1 | Western Pacific | Micronesia | 5.921290 | -162.09040 | 5.921290 | -162.09040 | GoogleMaps Palmyra Atoll | 27.90000 | Table 1 | Prevalence extracted using MetaDigitise in Rstudio, n = 20 | Pacific Ocean | 28.83150 | 28.8315 | 0.0586900 | 8 | 9 | 28.64667 | 28.625 | 0.1338217 | aut | 8 | summer | 8.9442720 | NA | 0.8000 | 0.80000 | 10 | Materials and Methods Coral Disease | NA | 1 | NA | Belt | 2 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Coral Disease | NA | 5 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2749939 | 302.11 | 0.000000 |
| 316 | EI0325 | CD049 | SI079 | 6.2522520 | % | 1.3873874 | Figure 4b | 2005 | Aug-Sep | Aug-Sep | Materials and Methods | Tabuaeran, Line Islands | Figure 1 | Western Pacific | Micronesia | 3.878780 | -159.31828 | 3.878780 | -159.31828 | GoogleMaps Tabuaeran | 27.50000 | Table 1 | Prevalence extracted using MetaDigitise in Rstudio, n = 20 | Pacific Ocean | 28.29500 | 28.2950 | 0.0494973 | 8 | 9 | 28.42767 | 28.435 | 0.1641225 | aut | 8 | summer | 6.2045850 | NA | 0.9000 | 0.80000 | 10 | Materials and Methods Coral Disease | NA | 1 | NA | Belt | 2 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Coral Disease | NA | 5 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7703476 | 301.54 | 2.192828 |
| 317 | EI0326 | CD049 | SI080 | 6.3243240 | % | 1.4234234 | Figure 4b | 2005 | Aug-Sep | Aug-Sep | Materials and Methods | Kiritimati, Line Islands | Figure 1 | Western Pacific | Micronesia | 1.886260 | -157.43060 | 1.965730 | -157.46071 | GoogleMaps Kiritimati | 27.10000 | Table 1 | Prevalence extracted using MetaDigitise in Rstudio, n = 20 | Pacific Ocean | 27.45150 | 27.4515 | 0.1110155 | 8 | 9 | 27.76967 | 27.723 | 0.4219400 | aut | 8 | summer | 6.3657430 | NA | 1.1000 | 0.80000 | 10 | Materials and Methods Coral Disease | NA | 1 | NA | Belt | 2 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Coral Disease | NA | 5 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3664398 | 301.17 | 0.000000 |
| 319 | EI0328 | CD051 | SI082 | 0.3523810 | % | 9.05E-02 | Figure 2a | 2014 | Oct-Nov | Oct-Nov | Materials and Methods Disease surveys | Filitheyo Faafu Atoll, Maldives | Figure 1 | Western Indian Ocean | Central Indian | 3.214300 | 73.03688 | 3.214300 | 73.03688 | GoogleMaps Filitheyo Island, Maldives | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 24 | Indian Ocean | 28.91500 | 28.9150 | 0.1060657 | 10 | 11 | 29.50800 | 29.433 | 0.0653841 | aut | 10 | fall | 0.4432410 | NA | NA | 1.20000 | 8 | Materials and Methods Disease surveys | NA | 1 | NA | Belt | 24 | 25.0000 | 2.00 | 50.0000 | Materials and Methods Disease surveys | NA | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3435669 | 302.68 | 0.000000 |
| 320 | EI0329 | CD051 | SI083 | 0.6428571 | % | 0.14285714 | Figure 2a | 2014 | Oct-Nov | Oct-Nov | Materials and Methods Disease surveys | Adanga Faafu Atoll, Maldives | Figure 1 | Western Indian Ocean | Central Indian | 3.134280 | 73.01831 | 3.134280 | 73.01831 | GoogleMaps, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 24 | Indian Ocean | 28.91500 | 28.9150 | 0.1060657 | 10 | 11 | 29.50800 | 29.433 | 0.0653841 | aut | 10 | fall | 0.6998542 | NA | NA | 1.20000 | 8 | Materials and Methods Disease surveys | NA | 1 | NA | Belt | 24 | 25.0000 | 2.00 | 50.0000 | Materials and Methods Disease surveys | NA | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3185730 | 302.67 | 0.000000 |
| 321 | EI0330 | CD051 | SI084 | 0.6333300 | % | 0.10952381 | Figure 2a | 2014 | Oct-Nov | Oct-Nov | Materials and Methods Disease surveys | Magoodhoo Faafu Atoll, Maldives | Figure 1 | Western Indian Ocean | Central Indian | 3.090470 | 72.96381 | 3.090470 | 72.96381 | GoogleMaps Magoodhoo, Maldives | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 24 | Indian Ocean | 28.92650 | 28.9265 | 0.1081873 | 10 | 11 | 29.58967 | 29.508 | 0.0728580 | aut | 10 | fall | 0.5365549 | NA | NA | 1.20000 | 8 | Materials and Methods Disease surveys | NA | 1 | NA | Belt | 24 | 25.0000 | 2.00 | 50.0000 | Materials and Methods Disease surveys | NA | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3328552 | 302.67 | 0.000000 |
| 322 | EI0331 | CD052 | SI085 | 1.5000000 | % | 1 | Results p151 | 2011 | Oct | Oct | Methods p151 | Barranglompo Spermonde Archipelago, South Sulawesi | Methods p151 | Coral Triangle & SE Asia | Southeast Asia | -5.046667 | 119.33000 | -5.046667 | 119.33000 | Methods p151, GoogleMaps | NA | NA | deep site | Pacific Ocean | 28.75500 | 28.7550 | NA | 10 | 10 | 29.08200 | 28.848 | 0.6656004 | spr | 4 | spring | NA | NA | NA | 0.09000 | 1 | Methods p151 | NA | 1 | NA | Belt | 3 | 15.0000 | 2.00 | 30.0000 | Methods p151 | NA | 5 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1735840 | 302.57 | 9.384250 |
| 323 | EI0332 | CD052 | SI085 | 4.6000000 | % | 6 | Results p151 | 2011 | Oct | Oct | Methods p151 | Barranglompo Spermonde Archipelago, South Sulawesi | Methods p151 | Coral Triangle & SE Asia | Southeast Asia | -5.046667 | 119.33000 | -5.046667 | 119.33000 | Methods p151, GoogleMaps | NA | NA | shallow site | Pacific Ocean | 28.75500 | 28.7550 | NA | 10 | 10 | 29.08200 | 28.848 | 0.6656004 | spr | 4 | spring | NA | NA | NA | 0.06000 | 1 | Methods p151 | NA | 1 | NA | Belt | 2 | 15.0000 | 2.00 | 30.0000 | Methods p151 | NA | 5 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1735840 | 302.57 | 9.384250 |
| 324 | EI0333 | CD053 | SI086 | 0.1517241 | % | 3.25E-02 | Figure 4a | 2011 | Jun-Sep | Jun-Sep | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.07700 | 28.9865 | 0.3758093 | 6 | 9 | 28.62267 | 28.333 | 0.5349637 | win | 12 | winter | 0.1379310 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2235641 | 302.56 | 1.241423 |
| 325 | EI0334 | CD053 | SI086 | 0.7655172 | % | 0.17230648 | Figure 4a | 2011 | Oct-Nov | Oct-Nov | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.62900 | 29.6290 | 0.1923326 | 10 | 11 | 28.62267 | 28.333 | 0.5349637 | spr | 4 | spring | 0.7310345 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3900146 | 302.56 | 0.000000 |
| 326 | EI0335 | CD053 | SI086 | 0.3241379 | % | 4.06E-02 | Figure 4a | 2012 | Dec-Mar | Dec-Mar | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.10125 | 28.8525 | 0.2945723 | 12 | 3 | 28.99167 | 28.855 | 0.2410559 | aut | 6 | summer | 0.1724138 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5635605 | 302.56 | 0.000000 |
| 327 | EI0336 | CD053 | SI086 | 0.1517241 | % | 4.71E-02 | Figure 4a | 2012 | Apr-May | Apr-May | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.62000 | 29.6200 | 0.1555630 | 4 | 5 | 28.99167 | 28.855 | 0.2410559 | aut | 10 | fall | 0.2000000 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8056946 | 302.56 | 0.000000 |
| 328 | EI0337 | CD053 | SI086 | 0.1172414 | % | 2.60E-02 | Figure 4a | 2011 | Jun-Sep | Jun-Sep | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.07700 | 28.9865 | 0.3758093 | 6 | 9 | 28.62267 | 28.333 | 0.5349637 | win | 12 | winter | 0.1103448 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2235641 | 302.56 | 1.241423 |
| 329 | EI0338 | CD053 | SI086 | 0.0620690 | % | 1.63E-02 | Figure 4a | 2011 | Oct-Nov | Oct-Nov | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.62900 | 29.6290 | 0.1923326 | 10 | 11 | 28.62267 | 28.333 | 0.5349637 | spr | 4 | spring | 0.0689655 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3900146 | 302.56 | 0.000000 |
| 330 | EI0339 | CD053 | SI086 | 0.0137931 | % | 4.88E-03 | Figure 4a | 2012 | Dec-Mar | Dec-Mar | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.10125 | 28.8525 | 0.2945723 | 12 | 3 | 28.99167 | 28.855 | 0.2410559 | aut | 6 | summer | 0.0206897 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5635605 | 302.56 | 0.000000 |
| 331 | EI0340 | CD053 | SI086 | 0.0068966 | % | 1.63E-03 | Figure 4a | 2012 | Apr-May | Apr-May | Figure 4a | Kepulauan Seribu, Indonesia | Materials and Methods 2.1 Study Site p106 | Coral Triangle & SE Asia | Southeast Asia | -5.600000 | 106.55069 | -5.600000 | 106.55069 | GoogleMaps Kepulauan Seribu, Indonesia | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 18 | Pacific Ocean | 29.62000 | 29.6200 | 0.1555630 | 4 | 5 | 28.99167 | 28.855 | 0.2410559 | aut | 10 | fall | 0.0068966 | NA | NA | 0.36000 | 6 | Results p106 | NA | 1 | NA | Belt | 18 | 20.0000 | 1.00 | 20.0000 | Materials and Methods 2.2.2 Coral disease abundance p106 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8056946 | 302.56 | 0.000000 |
| 332 | EI0341 | CD054 | SI087 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Gabuo PR Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.909560 | 100.33414 | -0.909560 | 100.33414 | Table 1 | 31.50000 | Table 2 | BBD, Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7539291 | 302.74 | 0.000000 |
| 333 | EI0342 | CD054 | SI088 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Pisang Is Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.997270 | 100.33865 | -0.997270 | 100.33865 | Table 1 | 31.00000 | Table 2 | BBD, Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6014099 | 302.75 | 0.000000 |
| 334 | EI0343 | CD054 | SI089 | 0.3088235 | % | NA | Figure 3 | 2014 | May | May | Materials and Methods p182 | Air PR Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.883980 | 100.21338 | -0.883980 | 100.21338 | Table 1 | 31.30000 | Table 2 | BBD, Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1149597 | 302.73 | 1.191418 |
| 335 | EI0344 | CD054 | SI090 | 0.4852941 | % | NA | Figure 3 | 2014 | May | May | Materials and Methods p182 | Sipakal PR Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.927640 | 100.25074 | -0.927640 | 100.25074 | Table 1 | 31.70000 | Table 2 | BBD, Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9078674 | 302.74 | 1.065695 |
| 336 | EI0345 | CD054 | SI091 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Pieh Is Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.877000 | 100.09838 | -0.877000 | 100.09838 | Table 1 | 30.20000 | Table 2 | BBD, Prevalence extracted using MetaDigitise in Rstudio, n = 6 | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.36000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 6 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6943054 | 302.71 | 2.407150 |
| 337 | EI0346 | CD054 | SI092 | 0.7352941 | % | NA | Figure 3 | 2014 | May | May | Materials and Methods p182 | Pandan Is Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.952850 | 100.14035 | -0.952850 | 100.14035 | Table 1 | 31.50000 | Table 2 | BBD, Prevalence extracted using MetaDigitise in Rstudio, n = 6 | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.36000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 6 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4353104 | 302.72 | 1.067141 |
| 338 | EI0347 | CD054 | SI087 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Gabuo PR Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.909560 | 100.33414 | -0.909560 | 100.33414 | Table 1 | 31.50000 | Table 2 | WS, Prevalence extracted using MetaDigitise in Rstudio, n = | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7539291 | 302.74 | 0.000000 |
| 339 | EI0348 | CD054 | SI088 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Pisang Is Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.997270 | 100.33865 | -0.997270 | 100.33865 | Table 1 | 31.00000 | Table 2 | WS, Prevalence extracted using MetaDigitise in Rstudio, n = | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6014099 | 302.75 | 0.000000 |
| 340 | EI0349 | CD054 | SI089 | 0.3088235 | % | NA | Figure 3 | 2014 | May | May | Materials and Methods p182 | Air PR Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.883980 | 100.21338 | -0.883980 | 100.21338 | Table 1 | 31.30000 | Table 2 | WS, Prevalence extracted using MetaDigitise in Rstudio, n = | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1149597 | 302.73 | 1.191418 |
| 341 | EI0350 | CD054 | SI090 | 0.3088235 | % | NA | Figure 3 | 2014 | May | May | Materials and Methods p182 | Sipakal PR Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.927640 | 100.25074 | -0.927640 | 100.25074 | Table 1 | 31.70000 | Table 2 | WS, Prevalence extracted using MetaDigitise in Rstudio, n = | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.18000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9078674 | 302.74 | 1.065695 |
| 342 | EI0351 | CD054 | SI091 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Pieh Is Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.877000 | 100.09838 | -0.877000 | 100.09838 | Table 1 | 30.20000 | Table 2 | WS, Prevalence extracted using MetaDigitise in Rstudio, n = | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.36000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 6 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6943054 | 302.71 | 2.407150 |
| 343 | EI0352 | CD054 | SI092 | 0.0000000 | % | 0 | Figure 3 | 2014 | May | May | Materials and Methods p182 | Pandan Is Padang Shelf Reef | Figure 1 | Eastern Indian Ocean | Southeast Asia | -0.952850 | 100.14035 | -0.952850 | 100.14035 | Table 1 | 31.50000 | Table 2 | WS, Prevalence extracted using MetaDigitise in Rstudio, n = | Indian Ocean | 30.03800 | 30.0380 | NA | 5 | 5 | 29.02767 | 28.990 | 0.0420280 | aut | 11 | fall | NA | NA | NA | 0.36000 | 1 | Materials and Methods p182 | NA | 1 | NA | Belt | 6 | 30.0000 | 2.00 | 60.0000 | Materials and Methods p182 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4353104 | 302.72 | 1.067141 |
| 344 | EI0353 | CD055 | SI093 | 11.0000000 | % | 0.9 | Table 1 | 1998 | Mar | Mar | Materials and Methods Abundance and distribution of diseased corals p63 | St Lucia, Caribbean | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 13.869460 | -61.08087 | 13.869460 | -61.08087 | GoogleMaps Anse Chastanet Beach | NA | NA | NA | Atlantic Ocean | 27.07000 | 27.0700 | NA | 3 | 3 | 28.82533 | 28.648 | 0.5912922 | spr | 3 | spring | NA | NA | NA | 5.40000 | 3 | Materials and Methods Abundance and distribution of diseased corals p63 | 3081 | 1 | NA | Belt | 27 | 40.0000 | 5.00 | 200.0000 | Materials and Methods Abundance and distribution of diseased corals p63 | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | In paper disease referred to as “plague” but described to leave behind white skeleton, so classified here as white syndrome (white plague) | 0.3432236 | 301.59 | 1.045712 |
| 345 | EI0354 | CD056 | SI094 | 2.2800000 | % | 0.39 | Results Disease types and prevalence p79 | 2010 | Jan | Jan | Figure 1 | Ningaloo Reef, Western Australia | Figure 1 | Eastern Indian Ocean | Australia | -22.495000 | 114.07500 | -22.675770 | 113.65518 | Materials and Methods Study area p77 averaged | NA | NA | coordinates not found in SST database - reselected from GoogleMaps | Indian Ocean | 25.71300 | 25.7130 | NA | 1 | 1 | 27.20367 | 27.078 | 1.3778048 | sum | 7 | summer | NA | NA | NA | 1.20000 | 10 | Figure 1 | NA | 1 | NA | Belt | 30 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Study design p77, Figure 1 | NA | 7 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “non-black cyanobacterial bands (OtCy)” labeled here as Cyano | 3.1900330 | 300.54 | 1.268564 |
| 346 | EI0355 | CD056 | SI095 | 0.8000000 | % | 0.2 | Figure 1a | 2009 | May | May | Figure 1 | Bill’s Bay, Western Australia | Figure 1 | Eastern Indian Ocean | Australia | -23.140000 | 113.76000 | -23.140000 | 113.76000 | Materials and Methods Study area p77 | NA | NA | NA | Indian Ocean | 25.68000 | 25.6800 | NA | 5 | 5 | 24.98033 | 25.018 | 0.7322267 | aut | 11 | fall | NA | NA | NA | 1.56000 | 13 | Figure 1 | NA | 1 | NA | Belt | 39 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Study design p77, Figure 1 | NA | 7 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “non-black cyanobacterial bands (OtCy)” labeled here as Cyano | 2.9400177 | 299.93 | 1.131433 |
| 347 | EI0356 | CD056 | SI095 | 4.1000000 | % | 0.8 | Figure 1a | 2010 | Jan | Jan | Figure 1 | Bill’s Bay, Western Australia | Figure 1 | Eastern Indian Ocean | Australia | -23.140000 | 113.76000 | -23.140000 | 113.76000 | Materials and Methods Study area p77 | NA | NA | NA | Indian Ocean | 25.01800 | 25.0180 | NA | 1 | 1 | 26.55933 | 26.440 | 1.3878540 | sum | 7 | summer | NA | NA | NA | 0.60000 | 5 | Figure 1 | NA | 1 | NA | Belt | 15 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Study design p77, Figure 1 | NA | 7 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “non-black cyanobacterial bands (OtCy)” labeled here as Cyano | 2.6057434 | 299.93 | 1.131433 |
| 348 | EI0357 | CD057 | SI096 | 0.1552000 | % | 4.30E-03 | Figure 4 | 1996 | 0 | 0 | Figure 4 | Florida Keys National Marine Sanctuary | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.703320 | -80.96646 | 24.703320 | -80.96646 | GoogleMaps West Turtle Shoal Reef, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 160 | Atlantic Ocean | 29.35300 | 29.3530 | NA | 7 | 7 | 29.16267 | 29.353 | 0.5240951 | sum | 7 | summer | NA | NA | NA | 6.40000 | 40 | Figure 1 | NA | 1 | NA | Belt | 160 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Static and dynamic trends in the geographic distribution of coral disease p2-3 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white plague” characterized as WS, “yellow blotch” characterized as YBD, “neoplasia” characterized as GA | 1.3979034 | 302.88 | 2.828563 |
| 349 | EI0358 | CD057 | SI096 | 0.6528000 | % | 4.55E-03 | Figure 4 | 1997 | 0 | 0 | Figure 4 | Florida Keys National Marine Sanctuary | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.703320 | -80.96646 | 24.703320 | -80.96646 | GoogleMaps West Turtle Shoal Reef, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 160 | Atlantic Ocean | 30.13000 | 30.1300 | NA | 7 | 7 | 29.83667 | 30.130 | 0.9399775 | sum | 7 | summer | NA | NA | NA | 6.40000 | 40 | Figure 1 | NA | 1 | NA | Belt | 160 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Static and dynamic trends in the geographic distribution of coral disease p2-3 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white plague” characterized as WS, “yellow blotch” characterized as YBD, “neoplasia” characterized as GA | 1.2671509 | 302.88 | 0.000000 |
| 350 | EI0359 | CD057 | SI096 | 0.8016000 | % | 4.93E-03 | Figure 4 | 1998 | 0 | 0 | Figure 4 | Florida Keys National Marine Sanctuary | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.703320 | -80.96646 | 24.703320 | -80.96646 | GoogleMaps West Turtle Shoal Reef, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 160 | Atlantic Ocean | 30.21500 | 30.2150 | NA | 7 | 7 | 29.98100 | 30.215 | 0.6913671 | sum | 7 | summer | NA | NA | NA | 6.40000 | 40 | Figure 1 | NA | 1 | NA | Belt | 160 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Static and dynamic trends in the geographic distribution of coral disease p2-3 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white plague” characterized as WS, “yellow blotch” characterized as YBD, “neoplasia” characterized as GA | 0.3574982 | 302.88 | 7.442838 |
| 351 | EI0360 | CD058 | SI097 | 65.1000000 | % | NA | Results 3.2 Disease abundance | 2002 | Jun-Aug | Jun-Aug | Results 3.2 Disease abundance | Florida Keys National Marine Sanctuary | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.703320 | -80.96646 | 24.703320 | -80.96646 | GoogleMaps West Turtle Shoal Reef, Figure 1 | NA | NA | NA | Atlantic Ocean | 29.24833 | 29.4950 | 0.8570490 | 6 | 8 | 29.24833 | 29.495 | 0.8570490 | sum | 6 | summer | NA | NA | NA | 0.28000 | 7 | Figure 1 | 238 | 1 | Admiral Patch Reef only for disease progression, not prevalence | Belt | 7 | 20.0000 | 2.00 | 40.0000 | Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Other diseases found, but prevalence only reported for DSS | 2.3356934 | 302.88 | 1.012853 |
| 352 | EI0361 | CD058 | SI097 | 66.1000000 | % | NA | Results 3.2 Disease abundance | 2003 | Jun-Aug | Jun-Aug | Results 3.2 Disease abundance | Florida Keys National Marine Sanctuary | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.703320 | -80.96646 | 24.703320 | -80.96646 | GoogleMaps West Turtle Shoal Reef, Figure 1 | NA | NA | NA | Atlantic Ocean | 29.34467 | 29.4180 | 0.5834666 | 6 | 8 | 29.34467 | 29.418 | 0.5834666 | sum | 6 | summer | NA | NA | NA | 0.28000 | 7 | Figure 1 | 157 | 1 | Admiral Patch Reef only for disease progression, not prevalence | Belt | 7 | 20.0000 | 2.00 | 40.0000 | Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Other diseases found, but prevalence only reported for DSS | 1.5714416 | 302.88 | 0.000000 |
| 353 | EI0362 | CD058 | SI097 | 82.5000000 | % | NA | Results 3.2 Disease abundance | 2004 | Jun-Aug | Jun-Aug | Results 3.2 Disease abundance | Florida Keys National Marine Sanctuary | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.703320 | -80.96646 | 24.703320 | -80.96646 | GoogleMaps West Turtle Shoal Reef, Figure 1 | NA | NA | NA | Atlantic Ocean | 29.64467 | 29.9630 | 0.6671268 | 6 | 8 | 29.64467 | 29.963 | 0.6671268 | sum | 6 | summer | NA | NA | NA | 0.28000 | 7 | Figure 1 | 299 | 1 | Admiral Patch Reef only for disease progression, not prevalence | Belt | 7 | 20.0000 | 2.00 | 40.0000 | Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Other diseases found, but prevalence only reported for DSS | 0.3135834 | 302.88 | 0.000000 |
| 354 | EI0363 | CD059 | SI098 | 15.4901960 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Kavaratti Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 10.568190 | 72.64148 | 10.568190 | 72.64148 | GoogleMaps Kavaratti Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.83630 | 27.9825 | 0.6952444 | 3 | 12 | 28.33100 | 28.145 | 0.6251107 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2378387 | 303.15 | 2.304249 |
| 355 | EI0364 | CD059 | SI099 | 11.3071900 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Agatti Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 10.869020 | 72.19553 | 10.869020 | 72.19553 | GoogleMaps Agatti Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.83630 | 27.9825 | 0.6952444 | 3 | 12 | 28.33100 | 28.145 | 0.6251107 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3021469 | 303.10 | 2.082838 |
| 356 | EI0365 | CD059 | SI100 | 19.2156860 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Thinnakara Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 10.947780 | 72.31874 | 10.947780 | 72.31874 | GoogleMaps Thinnakara Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.83630 | 27.9825 | 0.6952444 | 3 | 12 | 28.33100 | 28.145 | 0.6251107 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2114258 | 303.10 | 3.117147 |
| 357 | EI0366 | CD059 | SI101 | 36.8627450 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Minicoy Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 8.275070 | 73.04914 | 8.275070 | 73.04914 | GoogleMaps Minicoy Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.80950 | 27.9290 | 0.7588506 | 3 | 12 | 28.24267 | 28.043 | 0.5551184 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2614441 | 303.19 | 3.338541 |
| 358 | EI0367 | CD059 | SI102 | 10.9803920 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Kalpeni Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 10.078070 | 73.63037 | 10.078070 | 73.63037 | GoogleMaps Kalpeni Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.80800 | 27.8615 | 0.7676206 | 3 | 12 | 28.24267 | 28.043 | 0.6846939 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1664200 | 303.16 | 2.091409 |
| 359 | EI0368 | CD059 | SI103 | 7.0588240 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Chethlath Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 11.745800 | 72.69655 | 11.745800 | 72.69655 | GoogleMaps Chetlat Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.83270 | 27.9905 | 0.7024968 | 3 | 12 | 28.36700 | 28.193 | 0.6828340 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3810654 | 303.10 | 1.090003 |
| 360 | EI0369 | CD059 | SI104 | 33.5947710 | % | NA | Figure 3 | 2011 | Mar-Apr, Nov-Dec | Mar-Apr, Nov-Dec | Materials and Methods p2 | Bangaram Island, Lakshadweep, Indian Ocean | Material and Methods p2 | Western Indian Ocean | Central Indian | 10.937070 | 72.28794 | 10.937070 | 72.28794 | GoogleMaps Bangaram Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Indian Ocean | 28.83630 | 27.9825 | 0.6952444 | 3 | 12 | 28.33100 | 28.145 | 0.6251107 | multi | 3 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p2 | NA | 1 | NA | Line | 5 | 30.0000 | 1.00 | 30.0000 | Materials and Methods p2 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2514343 | 303.10 | 3.122854 |
| 361 | EI0370 | CD060 | SI105 | 16.7000000 | % | 2.1 | Table 1 | 1995 | Aug-Sep | Aug-Sep | Materials and Methods p148 | Northern Florida Keys | Materials and Methods p148 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.909940 | -80.75177 | 24.909940 | -80.75177 | GoogleMaps Florida Keys | NA | NA | Lat and Lon random point selected in Florida Keys - no specific location given in paper | Atlantic Ocean | 29.71400 | 29.7140 | 0.1046523 | 8 | 9 | 29.33333 | 29.615 | 0.5096653 | aut | 8 | summer | NA | NA | NA | 8.47800 | 7 | Materials and Methods p3 | NA | 0 | Site Num = reef number | Circle | 27 | 20.0000 | NA | 314.0000 | Materials and Methods p2-3 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white plague II” categorized as WS | 1.7842865 | 302.85 | 8.547099 |
| 362 | EI0371 | CD060 | SI105 | 3.2000000 | % | 1.5 | Table 1 | 1998 | Aug | Aug | Materials and Methods p148 | Northern Florida Keys | Materials and Methods p148 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.909940 | -80.75177 | 24.909940 | -80.75177 | GoogleMaps Florida Keys | NA | NA | Lat and Lon random point selected in Florida Keys - no specific location given in paper | Atlantic Ocean | 30.52500 | 30.5250 | NA | 8 | 8 | 29.98100 | 30.215 | 0.6913671 | sum | 8 | summer | NA | NA | NA | 6.28000 | 6 | Materials and Methods p3 | NA | 0 | Site Num = reef number | Circle | 20 | 20.0000 | NA | 314.0000 | Materials and Methods p2-3 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white plague II” categorized as WS | 0.9785767 | 302.85 | 17.969947 |
| 363 | EI0372 | CD060 | SI105 | 0.0000000 | % | 0 | Table 1 | 2002 | Aug | Aug | Materials and Methods p148 | Northern Florida Keys | Materials and Methods p148 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.909940 | -80.75177 | 24.909940 | -80.75177 | GoogleMaps Florida Keys | NA | NA | Lat and Lon random point selected in Florida Keys - no specific location given in paper | Atlantic Ocean | 29.95500 | 29.9550 | NA | 8 | 8 | 29.24833 | 29.495 | 0.8570490 | sum | 8 | summer | NA | NA | NA | 8.79200 | 9 | Materials and Methods p3 | NA | 0 | Site Num = reef number | Circle | 28 | 20.0000 | NA | 314.0000 | Materials and Methods p2-3 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white plague II” categorized as WS | 1.2357178 | 302.85 | 8.524272 |
| 364 | EI0373 | CD061 | SI106 | 23.7383200 | % | 5.099071 | Figure 2 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Eleuthera, Bahamas | Figure 2 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.969960 | -76.17788 | 24.969960 | -76.17788 | GoogleMaps Eleuthera | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Atlantic Ocean | 28.51367 | 28.4830 | 0.9363775 | 6 | 8 | 28.51367 | 28.483 | 0.9363775 | sum | 6 | summer | 11.4018700 | NA | NA | 0.11250 | 5 | Figure 1 | NA | 1 | NA | Belt | 5 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1271667 | 302.36 | 9.592828 |
| 365 | EI0374 | CD061 | SI107 | 11.9626200 | % | 4.681114 | Figure 2 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Cat Island, Bahamas | Figure 2 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.327070 | -75.44407 | 24.327070 | -75.44407 | GoogleMaps Cat Island | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Atlantic Ocean | 28.43133 | 28.4080 | 0.9352188 | 6 | 8 | 28.43133 | 28.408 | 0.9352188 | sum | 6 | summer | 10.4672900 | NA | NA | 0.11250 | 5 | Figure 1 | NA | 1 | NA | Belt | 5 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5014648 | 302.03 | 4.885679 |
| 366 | EI0375 | CD061 | SI108 | 4.1284400 | % | 0.9948948 | Figure 9 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Little Cayman, Cayman Islands | Figure 9 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.693290 | -80.03727 | 19.693290 | -80.03727 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 15 | Atlantic Ocean | 29.18267 | 29.0280 | 0.5903948 | 6 | 8 | 29.18267 | 29.028 | 0.5903948 | sum | 6 | summer | 3.8532110 | NA | NA | 0.33750 | 15 | Figure 1 | NA | 1 | NA | Belt | 15 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7603378 | 302.62 | 3.447131 |
| 367 | EI0376 | CD061 | SI109 | 3.7614680 | % | 0.9345409 | Figure 9 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Grand Cayman, Cayman Islands | Figure 9 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.326950 | -81.24179 | 19.326950 | -81.24179 | GoogleMaps Grand Cayman | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 17 | Atlantic Ocean | 29.04300 | 28.8880 | 0.5831597 | 6 | 8 | 29.04300 | 28.888 | 0.5831597 | sum | 6 | summer | 3.8532110 | NA | NA | 0.38250 | 17 | Figure 1 | NA | 1 | NA | Belt | 17 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7957153 | 302.47 | 5.154274 |
| 368 | EI0377 | CD061 | SI110 | 2.4770640 | % | 0.3481407 | Figure 9 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Turks Bank, Turks and Caicos Islands | Figure 9 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.419630 | -71.18804 | 21.419630 | -71.18804 | GoogleMaps Turks, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 10 | Atlantic Ocean | 28.20200 | 27.9230 | 0.6177162 | 6 | 8 | 28.20200 | 27.923 | 0.6177162 | sum | 6 | summer | 1.1009170 | NA | NA | 0.22500 | 10 | Figure 1 | NA | 1 | NA | Belt | 10 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0950165 | 301.74 | 0.000000 |
| 369 | EI0378 | CD061 | SI111 | 5.4128440 | % | 0.940367 | Figure 9 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Caicos Bank, Turks and Caicos Islands | Figure 9 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.575050 | -71.91941 | 21.575050 | -71.91941 | GoogleMaps Caicos, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 16 | Atlantic Ocean | 28.20200 | 27.9230 | 0.6177162 | 6 | 8 | 28.20200 | 27.923 | 0.6177162 | sum | 6 | summer | 3.7614680 | NA | NA | 0.36000 | 16 | Figure 1 | NA | 1 | NA | Belt | 16 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0417786 | 301.83 | 3.948539 |
| 370 | EI0379 | CD061 | SI112 | 12.1100920 | % | 3.5030978 | Figure 9 | 1999 | Jun-Aug | Jun-Aug | Materials and Methods | Mouchoir Bank, Turks and Caicos Islands | Figure 9 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.161110 | -70.77300 | 21.161110 | -70.77300 | GoogleMaps, random guess, Figure 1 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 2 | Atlantic Ocean | 28.16533 | 27.8930 | 0.6201024 | 6 | 8 | 28.16533 | 27.893 | 0.6201024 | sum | 6 | summer | 4.9541280 | NA | NA | 0.04500 | 2 | Figure 1 | NA | 1 | NA | Belt | 2 | 15.0000 | 1.50 | 22.5000 | Materials and Methods | NA | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8568115 | 301.69 | 0.000000 |
| 371 | EI0380 | CD062 | SI113 | 7.6635510 | % | 0.8411215 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | Plate Ledge, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 1.4568652 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 372 | EI0381 | CD062 | SI113 | 11.7757010 | % | 2.8037383 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | Coral Cascades, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 4.8562172 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 373 | EI0382 | CD062 | SI113 | 5.8878500 | % | 0.5607477 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | 2nd Point, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 0.9712434 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 374 | EI0383 | CD062 | SI113 | 6.3551400 | % | 3.4579439 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | 4th Point, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 5.9893346 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 375 | EI0384 | CD062 | SI113 | 4.9532710 | % | 1.3084112 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | Pams Point, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 2.2662347 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 376 | EI0385 | CD062 | SI113 | 18.6915890 | % | 6.5420561 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | Coral Canyons, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 11.3311735 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 377 | EI0386 | CD062 | SI113 | 11.5887850 | % | 1.2149533 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | Selinas Gutter, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 2.1043608 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 378 | EI0387 | CD062 | SI113 | 5.2336450 | % | 1.0280374 | Figure 3 | 2004 | Dec-Feb | Dec-Feb | Introduction | Plateau, Heron Reef | Figure 3 | Western Pacific | Australia | -23.450960 | 151.97031 | -23.450960 | 151.97031 | GoogleMaps Heron Reef | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 3 | Pacific Ocean | 27.09700 | 27.1880 | 0.6086233 | 12 | 2 | 27.09700 | 27.188 | 0.6086233 | aut | 6 | summer | 1.7806130 | NA | NA | 0.12000 | 1 | Figure 1 | NA | 1 | NA | Belt | 3 | 40.0000 | 1.00 | 40.0000 | Materials and Methods Spatial patterns of Acroporid white syndrome | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8010864 | 300.26 | 1.168559 |
| 379 | EI0388 | CD063 | SI114 | 41.6100000 | % | 3.93 | Results 3.2 Coral cover and disease | 2016 | Jul | Jul | Materials and Methods 2.1 Study area | Genting Island, Karimunjawa Archipelago | Materials and Methods 2.1 Study area | Coral Triangle & SE Asia | Southeast Asia | -5.845328 | 110.60047 | -5.845328 | 110.60047 | Materials and Methods 2.1 Study area, GoogleMaps | NA | NA | NA | Pacific Ocean | 29.43000 | 29.4300 | NA | 7 | 7 | 29.04967 | 29.048 | 0.5375023 | win | 1 | winter | NA | NA | NA | 0.15000 | 1 | Materials and Methods 2.1 Study area | 485 | 1 | NA | Belt | 3 | 25.0000 | 2.00 | 50.0000 | Materials and Methods 2.3 Live coral cover and disease prevalence | NA | 5 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2800064 | 302.74 | 4.997125 |
| 380 | EI0389 | CD063 | SI115 | 15.9200000 | % | 5.04 | Results 3.2 Coral cover and disease | 2016 | Jul | Jul | Materials and Methods 2.1 Study area | Sambangan Island, Karimunjawa Archipelago | Materials and Methods 2.1 Study area | Coral Triangle & SE Asia | Southeast Asia | -5.842778 | 110.58383 | -5.842778 | 110.58383 | Materials and Methods 2.1 Study area, GoogleMaps | NA | NA | Why is the latitude so off? - assumed typo, fixed to be -5.84278 (from -45.84278) | Pacific Ocean | 29.43000 | 29.4300 | NA | 7 | 7 | 29.04967 | 29.048 | 0.5375023 | win | 1 | winter | NA | NA | NA | 0.15000 | 1 | Materials and Methods 2.1 Study area | 453 | 1 | NA | Belt | 3 | 25.0000 | 2.00 | 50.0000 | Materials and Methods 2.3 Live coral cover and disease prevalence | NA | 5 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3307190 | 302.73 | 5.972867 |
| 381 | EI0390 | CD063 | SI116 | 6.8900000 | % | 1 | Results 3.2 Coral cover and disease | 2016 | Jul | Jul | Materials and Methods 2.1 Study area | Seruni Island, Karimunjawa Archipelago | Materials and Methods 2.1 Study area | Coral Triangle & SE Asia | Southeast Asia | -5.845311 | 110.60031 | -5.845311 | 110.60031 | Materials and Methods 2.1 Study area, GoogleMaps | NA | NA | NA | Pacific Ocean | 29.43000 | 29.4300 | NA | 7 | 7 | 29.04967 | 29.048 | 0.5375023 | win | 1 | winter | NA | NA | NA | 0.15000 | 1 | Materials and Methods 2.1 Study area | 317 | 1 | NA | Belt | 3 | 25.0000 | 2.00 | 50.0000 | Materials and Methods 2.3 Live coral cover and disease prevalence | NA | 4 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2800064 | 302.74 | 4.997125 |
| 382 | EI0391 | CD065 | SI117 | 8.7000000 | % | 2.8 | Discussion | 2010 | Dec | Dec | Material and Methods Field surveys and progression rate | Reunion Island, West Indian Ocean | Figure 1 | Western Indian Ocean | West Indian | -21.131505 | 55.25823 | -21.131505 | 55.25823 | Table 1, Averaged across four sites | NA | NA | NA | Indian Ocean | 26.98500 | 26.9850 | NA | 12 | 12 | 27.62333 | 27.860 | 0.5589353 | sum | 6 | summer | NA | NA | NA | 0.88000 | 4 | Material and Methods Field surveys and progression rate | 5363 | 1 | 4 stations, 3 sites, but use 4 because that’s more relative to the transect number; coral number aggregated from whole study,Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Material and Methods Field surveys and progression rate | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1057129 | 300.88 | 0.000000 |
| 383 | EI0392 | CD065 | SI117 | 1.4000000 | % | 1 | Discussion | 2011 | Oct | Oct | Material and Methods Field surveys and progression rate | Reunion Island, West Indian Ocean | Figure 1 | Western Indian Ocean | West Indian | -21.131505 | 55.25823 | -21.131505 | 55.25823 | Table 1, Averaged across four sites | NA | NA | NA | Indian Ocean | 24.18800 | 24.1880 | NA | 10 | 10 | 27.54467 | 27.473 | 0.7450898 | spr | 4 | spring | NA | NA | NA | 0.88000 | 4 | Material and Methods Field surveys and progression rate | 5363 | 1 | 4 stations, 3 sites, but use 4 because that’s more relative to the transect number; coral number aggregated from whole study, Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Material and Methods Field surveys and progression rate | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2917938 | 300.88 | 2.098552 |
| 384 | EI0393 | CD065 | SI117 | 7.7000000 | % | 2.5 | Discussion | 2012 | Jan | Jan | Material and Methods Field surveys and progression rate | Reunion Island, West Indian Ocean | Figure 1 | Western Indian Ocean | West Indian | -21.131505 | 55.25823 | -21.131505 | 55.25823 | Table 1, Averaged across four sites | NA | NA | NA | Indian Ocean | 27.47300 | 27.4730 | NA | 1 | 1 | 27.39800 | 27.518 | 0.7472615 | sum | 7 | summer | NA | NA | NA | 0.88000 | 4 | Material and Methods Field surveys and progression rate | 5363 | 1 | 4 stations, 3 sites, but use 4 because that’s more relative to the transect number; coral number aggregated from whole study,Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Material and Methods Field surveys and progression rate | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2842865 | 300.88 | 2.098552 |
| 385 | EI0394 | CD066 | SI118 | 6.8000000 | % | NA | Table 1 | 2010 | Sep | Sep | Table 1 | Reunion Island, West Indian Ocean | Table 1 | Western Indian Ocean | West Indian | -21.120000 | 55.25000 | -21.120000 | 55.25000 | Materials and Methods Disease surveys p250 | NA | NA | NA | Indian Ocean | 23.66000 | 23.6600 | NA | 9 | 9 | 27.62333 | 27.860 | 0.5589353 | spr | 3 | spring | 6.7000000 | NA | NA | 0.88000 | 4 | Table S1 | 23562 | 1 | coral_n aggregated over all years surveyed, Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Materials and Methods Disease surveys p250 | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 7 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1935730 | 300.88 | 0.000000 |
| 386 | EI0395 | CD066 | SI118 | 7.2000000 | % | NA | Table 1 | 2010 | Dec | Dec | Table 1 | Reunion Island, West Indian Ocean | Table 1 | Western Indian Ocean | West Indian | -21.120000 | 55.25000 | -21.120000 | 55.25000 | Materials and Methods Disease surveys p250 | NA | NA | NA | Indian Ocean | 26.98500 | 26.9850 | NA | 12 | 12 | 27.62333 | 27.860 | 0.5589353 | sum | 6 | summer | 6.4000000 | NA | NA | 0.88000 | 4 | Table S1 | 23562 | 1 | coral_n aggregated over all years surveyed, Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Materials and Methods Disease surveys p250 | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 7 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1057129 | 300.88 | 0.000000 |
| 387 | EI0396 | CD066 | SI118 | 8.3000000 | % | NA | Table 1 | 2011 | Oct | Oct | Table 1 | Reunion Island, West Indian Ocean | Table 1 | Western Indian Ocean | West Indian | -21.120000 | 55.25000 | -21.120000 | 55.25000 | Materials and Methods Disease surveys p250 | NA | NA | NA | Indian Ocean | 24.18800 | 24.1880 | NA | 10 | 10 | 27.54467 | 27.473 | 0.7450898 | spr | 4 | spring | 7.1000000 | NA | NA | 0.88000 | 4 | Table S1 | 23562 | 1 | coral_n aggregated over all years surveyed, Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Materials and Methods Disease surveys p250 | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 7 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2917938 | 300.88 | 2.098552 |
| 388 | EI0397 | CD066 | SI118 | 7.8000000 | % | NA | Table 1 | 2012 | Jan | Jan | Table 1 | Reunion Island, West Indian Ocean | Table 1 | Western Indian Ocean | West Indian | -21.120000 | 55.25000 | -21.120000 | 55.25000 | Materials and Methods Disease surveys p250 | NA | NA | NA | Indian Ocean | 27.47300 | 27.4730 | NA | 1 | 1 | 27.39800 | 27.518 | 0.7472615 | sum | 7 | summer | 6.2000000 | NA | NA | 0.88000 | 4 | Table S1 | 23562 | 1 | coral_n aggregated over all years surveyed, Sample area pooled to account for total area of all transect types | Belt | 8 | 15.0000 | 2.00 | 30.0000 | Materials and Methods Disease surveys p250 | Two different transect sizes utilized at reef flats vs reef slope, but both included in this disease prevalence, pooled transect number, averaged transect length and plot area | 7 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2842865 | 300.88 | 2.098552 |
| 389 | EI0398 | CD066 | SI119 | 3.9000000 | % | NA | Table 1 | 2011 | Feb | Feb | Table 1 | Sodwana Bay, South Africa | Table 1 | Western Indian Ocean | West Indian | -27.310000 | 32.41000 | -27.310130 | 32.76050 | Materials and Methods Disease surveys p250 | NA | NA | coordinates not found in SST dataset - reselected from GoogleMaps | Indian Ocean | 27.19000 | 27.1900 | NA | 2 | 2 | 26.60433 | 26.938 | 0.7642355 | sum | 8 | summer | 3.6000000 | NA | NA | 0.70000 | 7 | Table S1 | 17140 | 1 | coral_n aggregated over all years surveyed | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Disease surveys p250 | NA | 6 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | includes bleaching (see Table 2) | 1.6007233 | 300.18 | 1.138574 |
| 390 | EI0399 | CD066 | SI119 | 1.9000000 | % | NA | Table 1 | 2011 | Jul | Jul | Table 1 | Sodwana Bay, South Africa | Table 1 | Western Indian Ocean | West Indian | -27.310000 | 32.41000 | -27.310130 | 32.76050 | Materials and Methods Disease surveys p250 | NA | NA | coordinates not found in SST dataset - reselected from GoogleMaps | Indian Ocean | 22.72800 | 22.7280 | NA | 7 | 7 | 26.60433 | 26.938 | 0.7642355 | win | 1 | winter | 1.2000000 | NA | NA | 0.70000 | 7 | Table S1 | 17140 | 1 | coral_n aggregated over all years surveyed | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Disease surveys p250 | NA | 6 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | includes bleaching (see Table 2) | 0.7196350 | 300.18 | 1.138574 |
| 391 | EI0400 | CD066 | SI119 | 4.1000000 | % | NA | Table 1 | 2012 | Feb | Feb | Table 1 | Sodwana Bay, South Africa | Table 1 | Western Indian Ocean | West Indian | -27.310000 | 32.41000 | -27.310130 | 32.76050 | Materials and Methods Disease surveys p250 | NA | NA | coordinates not found in SST dataset - reselected from GoogleMaps | Indian Ocean | 27.14500 | 27.1450 | NA | 2 | 2 | 26.80533 | 27.058 | 0.7276789 | sum | 8 | summer | 2.0000000 | NA | NA | 0.70000 | 7 | Table S1 | 17140 | 1 | coral_n aggregated over all years surveyed | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Disease surveys p250 | NA | 6 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | includes bleaching (see Table 2) | 0.4578552 | 300.18 | 0.000000 |
| 392 | EI0401 | CD066 | SI119 | 5.7000000 | % | NA | Table 1 | 2012 | Jun | Jun | Table 1 | Sodwana Bay, South Africa | Table 1 | Western Indian Ocean | West Indian | -27.310000 | 32.41000 | -27.310130 | 32.76050 | Materials and Methods Disease surveys p250 | NA | NA | coordinates not found in SST dataset - reselected from GoogleMaps | Indian Ocean | 23.80500 | 23.8050 | NA | 6 | 6 | 26.80533 | 27.058 | 0.7276789 | win | 12 | winter | 3.2000000 | NA | NA | 0.70000 | 7 | Table S1 | 17140 | 1 | coral_n aggregated over all years surveyed | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Disease surveys p250 | NA | 6 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | includes bleaching (see Table 2) | 0.6893005 | 300.18 | 0.000000 |
| 393 | EI0402 | CD066 | SI120 | 2.3000000 | % | NA | Table 1 | 2011 | Aug | Aug | Table 1 | Mayotte, West Indian Ocean | Table 1 | Western Indian Ocean | West Indian | -12.820000 | 45.17000 | -12.820000 | 45.17000 | Materials and Methods Disease surveys p250 | NA | NA | NA | Indian Ocean | 25.92800 | 25.9280 | NA | 8 | 8 | 29.06267 | 28.855 | 0.2288364 | win | 2 | winter | 3.4000000 | NA | NA | 0.80000 | 8 | Table S1 | 19426 | 1 | coral_n aggregated over all years surveyed | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Disease surveys p250 | NA | 6 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5371399 | 302.40 | 0.000000 |
| 394 | EI0403 | CD066 | SI120 | 3.1000000 | % | NA | Table 1 | 2012 | Mar | Mar | Table 1 | Mayotte, West Indian Ocean | Table 1 | Western Indian Ocean | West Indian | -12.820000 | 45.17000 | -12.820000 | 45.17000 | Materials and Methods Disease surveys p250 | NA | NA | NA | Indian Ocean | 29.25000 | 29.2500 | NA | 3 | 3 | 28.79367 | 28.765 | 0.3608547 | aut | 9 | fall | 2.3000000 | NA | NA | 0.80000 | 8 | Table S1 | 19426 | 1 | coral_n aggregated over all years surveyed | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Disease surveys p250 | NA | 6 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2932205 | 302.40 | 0.000000 |
| 395 | EI0404 | CD067 | SI121 | 0.7000000 | % | 0.8 | Results p4 | 2009 | Jan-Apr | Jan-Apr | Table 2 | La Parguera Natural Reserve, Puerto Rico | Table 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.924525 | -67.02578 | 17.924525 | -67.02578 | Table 1 averaged, GoogleMaps | NA | Figure 4 | SST data extracted using MetaDigitise in Rstudio, n = 1440? | Atlantic Ocean | 26.14325 | 25.9015 | 0.3051594 | 1 | 4 | 28.49167 | 28.575 | 0.3867924 | spr | 1 | winter | NA | NA | NA | 0.10000 | 6 | Table 1 | NA | 0 | NA | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods 2.1 Temporal and spatial variability of CYBD Incidence in M Faveolata p2 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2903595 | 301.93 | 0.000000 |
| 396 | EI0405 | CD067 | SI121 | 1.5000000 | % | 1.1 | Results p4 | 2009 | Jun-Sep | Jun-Sep | Table 2 | La Parguera Natural Reserve, Puerto Rico | Table 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.924525 | -67.02578 | 17.924525 | -67.02578 | Table 1 averaged, GoogleMaps | NA | Figure 4 | SST data extracted using MetaDigitise in Rstudio, n = 1464? | Atlantic Ocean | 28.67375 | 28.7025 | 0.4820334 | 6 | 9 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | NA | NA | NA | 0.10000 | 6 | Table 1 | NA | 0 | NA | Belt | 5 | 10.0000 | 2.00 | 20.0000 | Materials and Methods 2.1 Temporal and spatial variability of CYBD Incidence in M Faveolata p2 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 397 | EI0406 | CD068 | SI122 | 1.0144930 | % | 4.1304348 | Figure 3 | 2008 | Dec-Feb | Dec-Feb | Figure 3 | Pelotas, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 14.3082460 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4799805 | 301.94 | 1.035709 |
| 398 | EI0407 | CD068 | SI122 | 1.0144930 | % | 4.1304348 | Figure 3 | 2008 | Jun-Aug | Jun-Aug | Figure 3 | Pelotas, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 14.3082460 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.6699829 | 301.94 | 0.000000 |
| 399 | EI0408 | CD068 | SI122 | 1.2318840 | % | 4.1304348 | Figure 3 | 2009 | Dec-Feb | Dec-Feb | Figure 3 | Pelotas, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 14.3082460 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2275162 | 301.94 | 0.000000 |
| 400 | EI0409 | CD068 | SI122 | 3.0434780 | % | 3.5507246 | Figure 3 | 2009 | Jun-Aug | Jun-Aug | Figure 3 | Pelotas, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 12.3000710 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3103561 | 301.94 | 1.035709 |
| 401 | EI0410 | CD068 | SI123 | 8.0434780 | % | 3.4782609 | Figure 3 | 2008 | Dec-Feb | Dec-Feb | Figure 3 | Enrique, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 12.0490490 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4671326 | 301.93 | 0.000000 |
| 402 | EI0411 | CD068 | SI123 | 7.0289860 | % | 2.6811594 | Figure 3 | 2008 | Jun-Aug | Jun-Aug | Figure 3 | Enrique, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 9.2878090 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.7207184 | 301.93 | 0.000000 |
| 403 | EI0412 | CD068 | SI123 | 15.0000000 | % | 7.3913043 | Figure 3 | 2009 | Dec-Feb | Dec-Feb | Figure 3 | Enrique, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 25.6042290 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2192841 | 301.93 | 0.000000 |
| 404 | EI0413 | CD068 | SI123 | 13.9855070 | % | 7.1014493 | Figure 3 | 2009 | Jun-Aug | Jun-Aug | Figure 3 | Enrique, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 24.6001420 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 405 | EI0414 | CD068 | SI124 | 15.0000000 | % | 3.2608696 | Figure 3 | 2008 | Dec-Feb | Dec-Feb | Figure 3 | Media Luna, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 11.2959840 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4671326 | 301.93 | 0.000000 |
| 406 | EI0415 | CD068 | SI124 | 16.9565220 | % | 3.6956522 | Figure 3 | 2008 | Jun-Aug | Jun-Aug | Figure 3 | Media Luna, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 12.8021150 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.7207184 | 301.93 | 0.000000 |
| 407 | EI0416 | CD068 | SI124 | 15.9420290 | % | 3.7681159 | Figure 3 | 2009 | Dec-Feb | Dec-Feb | Figure 3 | Media Luna, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 13.0531370 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2192841 | 301.93 | 0.000000 |
| 408 | EI0417 | CD068 | SI124 | 18.9855070 | % | 3.5507246 | Figure 3 | 2009 | Jun-Aug | Jun-Aug | Figure 3 | Media Luna, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 12.3000710 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 409 | EI0418 | CD068 | SI125 | 32.9710140 | % | 3.115942 | Figure 3 | 2008 | Dec-Feb | Dec-Feb | Figure 3 | Turrumote, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 10.7939400 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4671326 | 301.93 | 0.000000 |
| 410 | EI0419 | CD068 | SI125 | 29.9275360 | % | 6.0869565 | Figure 3 | 2008 | Jun-Aug | Jun-Aug | Figure 3 | Turrumote, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 21.0858360 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.7207184 | 301.93 | 0.000000 |
| 411 | EI0420 | CD068 | SI125 | 37.1739130 | % | 6.0869565 | Figure 3 | 2009 | Dec-Feb | Dec-Feb | Figure 3 | Turrumote, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 21.0858360 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2192841 | 301.93 | 0.000000 |
| 412 | EI0421 | CD068 | SI125 | 36.8840580 | % | 6.7391304 | Figure 3 | 2009 | Jun-Aug | Jun-Aug | Figure 3 | Turrumote, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 23.3450330 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 413 | EI0422 | CD068 | SI126 | 3.5507250 | % | 2.0289855 | Figure 3 | 2008 | Dec-Feb | Dec-Feb | Figure 3 | Buoy, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.47533 | 26.2830 | 0.5588973 | 12 | 2 | 28.52867 | 28.443 | 0.4624894 | aut | 12 | winter | 7.0286120 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4467773 | 301.90 | 0.000000 |
| 414 | EI0423 | CD068 | SI126 | 1.0144930 | % | 1.3043478 | Figure 3 | 2008 | Jun-Aug | Jun-Aug | Figure 3 | Buoy, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.52867 | 28.4430 | 0.4624894 | 6 | 8 | 28.52867 | 28.443 | 0.4624894 | sum | 6 | summer | 4.5183930 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.6807251 | 301.90 | 0.000000 |
| 415 | EI0424 | CD068 | SI126 | 2.5362320 | % | 1.6666667 | Figure 3 | 2009 | Dec-Feb | Dec-Feb | Figure 3 | Buoy, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.32600 | 27.1650 | 0.5902057 | 12 | 2 | 28.51334 | 28.600 | 0.3873415 | aut | 12 | winter | 5.7735030 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.1971588 | 301.90 | 0.000000 |
| 416 | EI0425 | CD068 | SI126 | 9.2028990 | % | 1.0144928 | Figure 3 | 2009 | Jun-Aug | Jun-Aug | Figure 3 | Buoy, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.51334 | 28.6000 | 0.3873415 | 6 | 8 | 28.51334 | 28.600 | 0.3873415 | sum | 6 | summer | 3.5143060 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3878632 | 301.90 | 0.000000 |
| 417 | EI0426 | CD068 | SI127 | 4.0579710 | % | 5.3623188 | Figure 3 | 2008 | Dec-Feb | Dec-Feb | Figure 3 | Weinberg, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.47533 | 26.2830 | 0.5588973 | 12 | 2 | 28.52867 | 28.443 | 0.4624894 | aut | 12 | winter | 18.5756170 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4467773 | 301.90 | 0.000000 |
| 418 | EI0427 | CD068 | SI127 | 0.0000000 | % | 0 | Figure 3 | 2008 | Jun-Aug | Jun-Aug | Figure 3 | Weinberg, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.52867 | 28.4430 | 0.4624894 | 6 | 8 | 28.52867 | 28.443 | 0.4624894 | sum | 6 | summer | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.6807251 | 301.90 | 0.000000 |
| 419 | EI0428 | CD068 | SI127 | 2.1014490 | % | 2.8985507 | Figure 3 | 2009 | Dec-Feb | Dec-Feb | Figure 3 | Weinberg, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.32600 | 27.1650 | 0.5902057 | 12 | 2 | 28.51334 | 28.600 | 0.3873415 | aut | 12 | winter | 10.0408740 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.1971588 | 301.90 | 0.000000 |
| 420 | EI0429 | CD068 | SI127 | 7.6811590 | % | 0.7246377 | Figure 3 | 2009 | Jun-Aug | Jun-Aug | Figure 3 | Weinberg, La Parguera, Puerto Rico | Figure 3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.51334 | 28.6000 | 0.3873415 | 6 | 8 | 28.51334 | 28.600 | 0.3873415 | sum | 6 | summer | 2.5102190 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3878632 | 301.90 | 0.000000 |
| 421 | EI0430 | CD068 | SI122 | 0.0000000 | % | 0 | Figure 6 | 2008 | Dec-Feb | Dec-Feb | Figure 6 | Pelotas, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4799805 | 301.94 | 1.035709 |
| 422 | EI0431 | CD068 | SI122 | 0.0000000 | % | 0 | Figure 6 | 2008 | Jun-Aug | Jun-Aug | Figure 6 | Pelotas, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.6699829 | 301.94 | 0.000000 |
| 423 | EI0432 | CD068 | SI122 | 0.0000000 | % | 0 | Figure 6 | 2009 | Dec-Feb | Dec-Feb | Figure 6 | Pelotas, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2275162 | 301.94 | 0.000000 |
| 424 | EI0433 | CD068 | SI122 | 0.0000000 | % | 0 | Figure 6 | 2009 | Jun-Aug | Jun-Aug | Figure 6 | Pelotas, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3103561 | 301.94 | 1.035709 |
| 425 | EI0434 | CD068 | SI123 | 0.0000000 | % | 0 | Figure 6 | 2008 | Dec-Feb | Dec-Feb | Figure 6 | Enrique, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4671326 | 301.93 | 0.000000 |
| 426 | EI0435 | CD068 | SI123 | 0.0000000 | % | 0 | Figure 6 | 2008 | Jun-Aug | Jun-Aug | Figure 6 | Enrique, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.7207184 | 301.93 | 0.000000 |
| 427 | EI0436 | CD068 | SI123 | 0.0000000 | % | 0 | Figure 6 | 2009 | Dec-Feb | Dec-Feb | Figure 6 | Enrique, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2192841 | 301.93 | 0.000000 |
| 428 | EI0437 | CD068 | SI123 | 0.0000000 | % | 0 | Figure 6 | 2009 | Jun-Aug | Jun-Aug | Figure 6 | Enrique, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Inner-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 429 | EI0438 | CD068 | SI124 | 15.9183673 | % | 5.9183673 | Figure 6 | 2008 | Dec-Feb | Dec-Feb | Figure 6 | Media Luna, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 20.5018259 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4671326 | 301.93 | 0.000000 |
| 430 | EI0439 | CD068 | SI124 | 12.7040816 | % | 4.2346939 | Figure 6 | 2008 | Jun-Aug | Jun-Aug | Figure 6 | Media Luna, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 14.6694099 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.7207184 | 301.93 | 0.000000 |
| 431 | EI0440 | CD068 | SI124 | 2.2959184 | % | 1.0204082 | Figure 6 | 2009 | Dec-Feb | Dec-Feb | Figure 6 | Media Luna, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 3.5347976 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2192841 | 301.93 | 0.000000 |
| 432 | EI0441 | CD068 | SI124 | 0.9693878 | % | 0.5102041 | Figure 6 | 2009 | Jun-Aug | Jun-Aug | Figure 6 | Media Luna, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | Materials and Methods Mid-Shelf Reefs p83 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 1.7673988 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 433 | EI0442 | CD068 | SI125 | 22.0408163 | % | 3.622449 | Figure 6 | 2008 | Dec-Feb | Dec-Feb | Figure 6 | Turrumote, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.44834 | 26.2800 | 0.5424561 | 12 | 2 | 28.48933 | 28.395 | 0.4313078 | aut | 12 | winter | 12.5485314 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4671326 | 301.93 | 0.000000 |
| 434 | EI0443 | CD068 | SI125 | 15.6122449 | % | 4.0306122 | Figure 6 | 2008 | Jun-Aug | Jun-Aug | Figure 6 | Turrumote, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.48933 | 28.3950 | 0.4313078 | 6 | 8 | 28.48933 | 28.395 | 0.4313078 | sum | 6 | summer | 13.9624504 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.7207184 | 301.93 | 0.000000 |
| 435 | EI0444 | CD068 | SI125 | 24.7448980 | % | 4.1326531 | Figure 6 | 2009 | Dec-Feb | Dec-Feb | Figure 6 | Turrumote, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.28600 | 27.1280 | 0.5910563 | 12 | 2 | 28.49167 | 28.575 | 0.3867924 | aut | 12 | winter | 14.3159301 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.2192841 | 301.93 | 0.000000 |
| 436 | EI0445 | CD068 | SI125 | 24.4387755 | % | 4.1326531 | Figure 6 | 2009 | Jun-Aug | Jun-Aug | Figure 6 | Turrumote, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | Materials and Methods Mid-Shelf Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.49167 | 28.5750 | 0.3867924 | 6 | 8 | 28.49167 | 28.575 | 0.3867924 | sum | 6 | summer | 14.3159301 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3128586 | 301.93 | 0.000000 |
| 437 | EI0446 | CD068 | SI126 | 0.0000000 | % | 0 | Figure 6 | 2008 | Dec-Feb | Dec-Feb | Figure 6 | Buoy, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.47533 | 26.2830 | 0.5588973 | 12 | 2 | 28.52867 | 28.443 | 0.4624894 | aut | 12 | winter | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4467773 | 301.90 | 0.000000 |
| 438 | EI0447 | CD068 | SI126 | 1.0714286 | % | 0.1020408 | Figure 6 | 2008 | Jun-Aug | Jun-Aug | Figure 6 | Buoy, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.52867 | 28.4430 | 0.4624894 | 6 | 8 | 28.52867 | 28.443 | 0.4624894 | sum | 6 | summer | 0.3534798 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.6807251 | 301.90 | 0.000000 |
| 439 | EI0448 | CD068 | SI126 | 0.5612245 | % | 0.1530612 | Figure 6 | 2009 | Dec-Feb | Dec-Feb | Figure 6 | Buoy, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.32600 | 27.1650 | 0.5902057 | 12 | 2 | 28.51334 | 28.600 | 0.3873415 | aut | 12 | winter | 0.5302196 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.1971588 | 301.90 | 0.000000 |
| 440 | EI0449 | CD068 | SI126 | 1.7857143 | % | 0.255102 | Figure 6 | 2009 | Jun-Aug | Jun-Aug | Figure 6 | Buoy, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.885167 | -66.99183 | 17.885167 | -66.99183 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.51334 | 28.6000 | 0.3873415 | 6 | 8 | 28.51334 | 28.600 | 0.3873415 | sum | 6 | summer | 0.8836994 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3878632 | 301.90 | 0.000000 |
| 441 | EI0450 | CD068 | SI127 | 2.0408163 | % | 0.1020408 | Figure 6 | 2008 | Dec-Feb | Dec-Feb | Figure 6 | Weinberg, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 26.47533 | 26.2830 | 0.5588973 | 12 | 2 | 28.52867 | 28.443 | 0.4624894 | aut | 12 | winter | 0.3534798 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.4467773 | 301.90 | 0.000000 |
| 442 | EI0451 | CD068 | SI127 | 0.0000000 | % | 0 | Figure 6 | 2008 | Jun-Aug | Jun-Aug | Figure 6 | Weinberg, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.52867 | 28.4430 | 0.4624894 | 6 | 8 | 28.52867 | 28.443 | 0.4624894 | sum | 6 | summer | 0.0000000 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.6807251 | 301.90 | 0.000000 |
| 443 | EI0452 | CD068 | SI127 | 0.4591837 | % | 0.5102041 | Figure 6 | 2009 | Dec-Feb | Dec-Feb | Figure 6 | Weinberg, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 27.32600 | 27.1650 | 0.5902057 | 12 | 2 | 28.51334 | 28.600 | 0.3873415 | aut | 12 | winter | 1.7673988 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.1971588 | 301.90 | 0.000000 |
| 444 | EI0453 | CD068 | SI127 | 0.2040816 | % | 0.3061224 | Figure 6 | 2009 | Jun-Aug | Jun-Aug | Figure 6 | Weinberg, La Parguera, Puerto Rico | Figure 6 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | Materials and Methods Shelf-Edge Reefs p84 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 12 | Atlantic Ocean | 28.51334 | 28.6000 | 0.3873415 | 6 | 8 | 28.51334 | 28.600 | 0.3873415 | sum | 6 | summer | 1.0604393 | NA | NA | 0.24000 | 1 | Figure 1 | NA | 0 | NA | Belt | 12 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Temporal and spatial variability in prevalence of CYBD in O. faveolata and O. franski p85 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | in paper as “caribbean yellow band disease” classified as YBD | 0.3878632 | 301.90 | 0.000000 |
| 445 | EI0454 | CD069 | SI128 | 74.6800000 | % | 3.61 | Results p23 | 2013 | May | May | Materials and Methods Study area p21 | Panjang Island, Java Sea, Indonesia | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -6.579083 | 110.62910 | -6.579083 | 110.62910 | Materials and Methods Study area p21, GoogleMaps | NA | NA | NA | Pacific Ocean | 30.12000 | 30.1200 | NA | 5 | 5 | 28.86267 | 28.708 | 0.4791047 | aut | 11 | fall | NA | NA | NA | 0.10000 | 1 | Figure 1 | 287 | 1 | coral_n aggregated over whole study | Belt | 2 | 25.0000 | 2.00 | 50.0000 | Materials and Methods Survey method p22 | NA | 4 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | White plague classified as WS | 0.4914398 | 303.01 | 0.000000 |
| 446 | EI0455 | CD069 | SI128 | 74.0700000 | % | 8.39 | Results p23 | 2013 | Nov | Nov | Materials and Methods Study area p21 | Panjang Island, Java Sea, Indonesia | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -6.579083 | 110.62910 | -6.579083 | 110.62910 | Materials and Methods Study area p21, GoogleMaps | NA | NA | NA | Pacific Ocean | 29.86300 | 29.8630 | NA | 11 | 11 | 28.86267 | 28.708 | 0.4791047 | spr | 5 | spring | NA | NA | NA | 0.10000 | 1 | Figure 1 | 287 | 1 | coral_n aggregated over whole study | Belt | 2 | 25.0000 | 2.00 | 50.0000 | Materials and Methods Survey method p22 | NA | 4 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | White plague classified as WS | 0.4360886 | 303.01 | 0.000000 |
| 447 | EI0456 | CD070 | SI129 | 2.5781250 | % | NA | Figure 4 | 2010 | Jan | Jan | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 27.78000 | 27.7800 | NA | 1 | 1 | 28.84533 | 28.833 | 0.4036409 | win | 1 | winter | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.8999939 | 303.61 | 1.017137 |
| 448 | EI0457 | CD070 | SI129 | 3.6718750 | % | NA | Figure 4 | 2010 | Feb | Feb | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 28.17800 | 28.1780 | NA | 2 | 2 | 28.84533 | 28.833 | 0.4036409 | win | 2 | winter | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.8999939 | 303.61 | 1.017137 |
| 449 | EI0458 | CD070 | SI129 | 4.6093750 | % | NA | Figure 4 | 2010 | Mar | Mar | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 29.39500 | 29.3950 | NA | 3 | 3 | 28.84533 | 28.833 | 0.4036409 | spr | 3 | spring | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.8999939 | 303.61 | 1.017137 |
| 450 | EI0459 | CD070 | SI129 | 6.1718750 | % | NA | Figure 4 | 2010 | Apr | Apr | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 30.44500 | 30.4450 | NA | 4 | 4 | 28.84533 | 28.833 | 0.4036409 | spr | 4 | spring | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 2.2217560 | 303.61 | 1.017137 |
| 451 | EI0460 | CD070 | SI129 | 8.2031250 | % | NA | Figure 4 | 2010 | May | May | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 30.40800 | 30.4080 | NA | 5 | 5 | 28.84533 | 28.833 | 0.4036409 | spr | 5 | spring | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.3814392 | 303.61 | 4.149999 |
| 452 | EI0461 | CD070 | SI129 | 9.7656250 | % | NA | Figure 4 | 2010 | Jun | Jun | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 29.25500 | 29.2550 | NA | 6 | 6 | 28.84533 | 28.833 | 0.4036409 | sum | 6 | summer | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.3814392 | 303.61 | 4.149999 |
| 453 | EI0462 | CD070 | SI129 | 11.2500000 | % | NA | Figure 4 | 2010 | Jul | Jul | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 28.83300 | 28.8330 | NA | 7 | 7 | 28.84533 | 28.833 | 0.4036409 | sum | 7 | summer | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.0507050 | 303.61 | 4.149999 |
| 454 | EI0463 | CD070 | SI129 | 12.2656250 | % | NA | Figure 4 | 2010 | Aug | Aug | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 28.44800 | 28.4480 | NA | 8 | 8 | 28.84533 | 28.833 | 0.4036409 | sum | 8 | summer | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.0507050 | 303.61 | 4.149999 |
| 455 | EI0464 | CD070 | SI129 | 13.1250000 | % | NA | Figure 4 | 2010 | Sep | Sep | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 28.52000 | 28.5200 | NA | 9 | 9 | 28.84533 | 28.833 | 0.4036409 | aut | 9 | fall | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.1628723 | 303.61 | 4.149999 |
| 456 | EI0465 | CD070 | SI129 | 13.9062500 | % | NA | Figure 4 | 2010 | Oct | Oct | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 28.56500 | 28.5650 | NA | 10 | 10 | 28.84533 | 28.833 | 0.4036409 | aut | 10 | fall | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.1628723 | 303.61 | 4.149999 |
| 457 | EI0466 | CD070 | SI129 | 14.4531250 | % | NA | Figure 4 | 2010 | Nov | Nov | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 28.29300 | 28.2930 | NA | 11 | 11 | 28.84533 | 28.833 | 0.4036409 | aut | 11 | fall | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.1628723 | 303.61 | 4.149999 |
| 458 | EI0467 | CD070 | SI129 | 14.9218750 | % | NA | Figure 4 | 2010 | Dec | Dec | Figure 4 | Palk Bay, Indian Ocean | Figure 1 | Eastern Indian Ocean | Central Indian | 9.283333 | 79.21389 | 9.283333 | 79.21389 | Materials and Methods Study site p64, averaged two longitudes, GoogleMaps conversion to decimal | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 40 | Indian Ocean | 27.59500 | 27.5950 | NA | 12 | 12 | 28.84533 | 28.833 | 0.4036409 | win | 12 | winter | NA | NA | NA | 3.20000 | 5 | Figure 1 | 1930 | 1 | NA | Belt | 40 | 20.0000 | 4.00 | 80.0000 | Materials and Methods Field data collection p65 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Acropora white syndrome categorized as WS | 0.3614502 | 303.61 | 4.149999 |
| 459 | EI0468 | CD034 | SI130 | 19.1000000 | % | 0.04 | Results Coral health p299 | 2007 | Oct-Dec | Oct-Dec | Methods In situ sampling protocols p293 | Hind Bank Marine Conservation District, Puerto Rican Shelf, US Virgin Islands | Methods Study location and sampling stratification p291 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.219110 | -65.03766 | 18.219110 | -65.03766 | GoogleMaps Hind Bank Marine Conservation District | NA | NA | NA | Atlantic Ocean | 28.08700 | 28.1500 | 0.8941660 | 10 | 12 | 28.82534 | 28.913 | 0.2153284 | aut | 10 | fall | NA | NA | NA | 2.40000 | 80 | Methods Study location and sampling stratification p291 | 1251 | 1 | NA | Line | 80 | 30.0000 | 1.00 | 30.0000 | Methods In situ sampling protocols p292 | Assume 1 transect per site because not stated otherwise | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | White plague classified as WS | 0.2989120 | 301.60 | 2.192823 |
| 460 | EI0469 | CD071 | SI131 | 1.3975155 | % | 0.26708075 | Figure 3b | 2011 | Feb | Feb | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 25.47619 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 24.47800 | 24.4780 | NA | 2 | 2 | 25.54367 | 25.470 | 0.2993762 | win | 2 | winter | 1.6891669 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.2864227 | 300.05 | 0.000000 |
| 461 | EI0470 | CD071 | SI131 | 1.3105590 | % | 0.28571429 | Figure 3b | 2011 | Mar | Mar | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 24.80952 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 24.42300 | 24.4230 | NA | 3 | 3 | 25.54367 | 25.470 | 0.2993762 | spr | 3 | spring | 1.8070158 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.2864227 | 300.05 | 0.000000 |
| 462 | EI0471 | CD071 | SI131 | 1.6894410 | % | 0.28571429 | Figure 3b | 2011 | Apr | Apr | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 26.58333 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 24.82300 | 24.8230 | NA | 4 | 4 | 25.54367 | 25.470 | 0.2993762 | spr | 4 | spring | 1.8070158 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.1878510 | 300.05 | 0.000000 |
| 463 | EI0472 | CD071 | SI131 | 2.0621118 | % | 0.36024845 | Figure 3b | 2011 | May | May | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 25.85714 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 25.24800 | 25.2480 | NA | 5 | 5 | 25.54367 | 25.470 | 0.2993762 | spr | 5 | spring | 2.2784112 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.1878510 | 300.05 | 0.000000 |
| 464 | EI0473 | CD071 | SI131 | 2.4534161 | % | 0.31677019 | Figure 3b | 2011 | Jun | Jun | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 26.00000 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 25.28800 | 25.2880 | NA | 6 | 6 | 25.54367 | 25.470 | 0.2993762 | sum | 6 | summer | 2.0034306 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.1764221 | 300.05 | 0.000000 |
| 465 | EI0474 | CD071 | SI131 | 1.6397516 | % | 0.26086957 | Figure 3b | 2011 | Aug | Aug | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 26.57143 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 25.87300 | 25.8730 | NA | 8 | 8 | 25.54367 | 25.470 | 0.2993762 | sum | 8 | summer | 1.6498840 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.1764221 | 300.05 | 0.000000 |
| 466 | EI0475 | CD071 | SI131 | 2.0310559 | % | 0.35403727 | Figure 3b | 2011 | Sep | Sep | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 26.88095 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 26.41500 | 26.4150 | NA | 9 | 9 | 25.54367 | 25.470 | 0.2993762 | aut | 9 | fall | 2.2391283 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.4264450 | 300.05 | 0.000000 |
| 467 | EI0476 | CD071 | SI131 | 1.2422360 | % | 0.37267081 | Figure 3b | 2011 | Oct | Oct | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 25.75000 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 26.34800 | 26.3480 | NA | 10 | 10 | 25.54367 | 25.470 | 0.2993762 | aut | 10 | fall | 2.3569771 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.1285706 | 300.05 | 0.000000 |
| 468 | EI0477 | CD071 | SI131 | 0.6273292 | % | 0.22360248 | Figure 3b | 2011 | Nov | Nov | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 23.92857 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 25.56000 | 25.5600 | NA | 11 | 11 | 25.54367 | 25.470 | 0.2993762 | aut | 11 | fall | 1.4141863 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.2021484 | 300.05 | 0.000000 |
| 469 | EI0478 | CD071 | SI131 | 0.5155280 | % | 0.1863354 | Figure 3b | 2011 | Dec | Dec | Figure 3b | Coconut Island Marine Reserve, Kaneohe Bay, Hawaii | Materials and Methods Prevalence and spatial distribution p60 | Western Pacific | Polynesia | 21.433333 | -157.78333 | 21.433333 | -157.78333 | Materials and Methods Prevalence and spatial distribution p60, GoogleMaps | 23.40476 | Fig 3b | Prevalence and temperature extracted using MetaDigitise in Rstudio, n = 40 | Pacific Ocean | 24.49800 | 24.4980 | NA | 12 | 12 | 25.54367 | 25.470 | 0.2993762 | win | 12 | winter | 1.1784886 | NA | NA | 0.80000 | 8 | Figure 2 | NA | 0 | NA | Belt | 40 | 10.0000 | 2.00 | 20.0000 | Materials and Method Prevalence and spatial distribution p60-61 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NA | 0.0843048 | 300.05 | 0.000000 |
| 470 | EI0479 | CD072 | SI132 | 28.0000000 | % | 11 | Results Growth anomalies (GAs) on corals | 2012 | Jul | Jul | Materials and Methods | Qeshm Island | Materials and Methods | Western Indian Ocean | Middle East | 26.688974 | 55.94352 | 26.688974 | 55.94352 | Figure 1, GoogleMaps | NA | NA | NA | Indian Ocean | 32.56000 | 32.5600 | NA | 7 | 7 | 31.97200 | 32.560 | 1.0384282 | sum | 7 | summer | NA | NA | NA | 0.24000 | 1 | Figure 1 | NA | 1 | NA | Belt | 8 | 30.0000 | 1.00 | 30.0000 | Materials and Methods | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3781967 | 305.68 | 0.000000 |
| 471 | EI0480 | CD072 | SI132 | 21.0000000 | % | 13 | Results Growth anomalies (GAs) on corals | 2012 | Jul | Jul | Materials and Methods | Qeshm Island | Materials and Methods | Western Indian Ocean | Middle East | 26.688974 | 55.94352 | 26.688974 | 55.94352 | Figure 1, GoogleMaps | NA | NA | NA | Indian Ocean | 32.56000 | 32.5600 | NA | 7 | 7 | 31.97200 | 32.560 | 1.0384282 | sum | 7 | summer | NA | NA | NA | 0.24000 | 1 | Figure 1 | NA | 1 | NA | Belt | 8 | 30.0000 | 1.00 | 30.0000 | Materials and Methods | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3781967 | 305.68 | 0.000000 |
| 472 | EI0481 | CD072 | SI132 | 37.0000000 | % | 7 | Results Growth anomalies (GAs) on corals | 2013 | Jul-Aug | Jul-Aug | Materials and Methods | Qeshm Island | Materials and Methods | Western Indian Ocean | Middle East | 26.688974 | 55.94352 | 26.688974 | 55.94352 | Figure 1, GoogleMaps | NA | NA | NA | Indian Ocean | 31.77150 | 31.7715 | 0.2524360 | 7 | 8 | 31.36767 | 31.593 | 0.7218769 | sum | 7 | summer | NA | NA | NA | 0.24000 | 1 | Figure 1 | NA | 1 | NA | Belt | 8 | 30.0000 | 1.00 | 30.0000 | Materials and Methods | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7435761 | 305.68 | 0.000000 |
| 473 | EI0482 | CD072 | SI132 | 23.0000000 | % | 12 | Results Growth anomalies (GAs) on corals | 2013 | Jul-Aug | Jul-Aug | Materials and Methods | Qeshm Island | Materials and Methods | Western Indian Ocean | Middle East | 26.688974 | 55.94352 | 26.688974 | 55.94352 | Figure 1, GoogleMaps | NA | NA | NA | Indian Ocean | 31.77150 | 31.7715 | 0.2524360 | 7 | 8 | 31.36767 | 31.593 | 0.7218769 | sum | 7 | summer | NA | NA | NA | 0.24000 | 1 | Figure 1 | NA | 1 | NA | Belt | 8 | 30.0000 | 1.00 | 30.0000 | Materials and Methods | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7435761 | 305.68 | 0.000000 |
| 474 | EI0483 | CD073 | SI133 | 0.7700000 | % | 0.23 | Table 1 | 2016 | Jan-Apr | Jan-Apr | Materials and Methods p212 | Johnston Atoll | Materials and Methods p212 | Western Pacific | Micronesia | 16.757160 | -169.53308 | 16.757160 | -169.53308 | GoogleMaps Johnston Atoll | NA | NA | NA | Pacific Ocean | 26.09325 | 25.9625 | 0.2278867 | 1 | 4 | 28.00167 | 27.930 | 0.5808258 | spr | 1 | winter | NA | NA | NA | 0.05000 | 18 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p214 | NA | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7414246 | 301.15 | 6.192819 |
| 475 | EI0484 | CD073 | SI134 | 0.1600000 | % | 0.05 | Table 1 | 2017 | Apr-May | Apr-May | Materials and Methods p212 | Wake Atoll | Materials and Methods p212 | Western Pacific | Micronesia | 22.572930 | 166.45558 | 22.572930 | 166.45558 | GoogleMaps Wake Atoll | NA | NA | NA | Pacific Ocean | 26.38150 | 26.3815 | 0.3938593 | 4 | 5 | 28.90533 | 29.133 | 0.5221560 | spr | 4 | spring | NA | NA | NA | 0.15000 | 12 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 3.00 | 75.0000 | Materials and Methods p214 | NA | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0414352 | 301.67 | 2.225706 |
| 476 | EI0485 | CD073 | SI135 | 0.0600000 | % | 0.01 | Table 1 | 2016 | Jan-Apr | Jan-Apr | Materials and Methods p212 | Baker Island | Materials and Methods p212 | Western Pacific | Micronesia | 4.760190 | -177.53317 | 4.760190 | -177.53317 | GoogleMaps Baker Island | NA | NA | NA | Pacific Ocean | 28.91000 | 28.8550 | 0.1253655 | 1 | 4 | 29.63433 | 29.615 | 0.1023782 | spr | 1 | winter | NA | NA | NA | 0.15000 | 6 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 3.00 | 75.0000 | Materials and Methods p214 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1943359 | 302.52 | 0.000000 |
| 477 | EI0486 | CD073 | SI136 | 0.0300000 | % | 0.02 | Table 1 | 2016 | Jan-Apr | Jan-Apr | Materials and Methods p212 | Howland Island | Materials and Methods p212 | Western Pacific | Micronesia | 4.844480 | -178.02393 | 4.844480 | -178.02393 | GoogleMaps Howland Island | NA | NA | NA | Pacific Ocean | 28.87850 | 28.8230 | 0.1387244 | 1 | 4 | 29.64933 | 29.625 | 0.1134736 | spr | 1 | winter | NA | NA | NA | 0.15000 | 8 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 3.00 | 75.0000 | Materials and Methods p214 | NA | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8343048 | 302.51 | 0.000000 |
| 478 | EI0487 | CD073 | SI137 | 0.0400000 | % | 0.02 | Table 1 | 2016 | Jan-Apr | Jan-Apr | Materials and Methods p212 | Jarvis Island | Materials and Methods p212 | Western Pacific | Micronesia | 5.070120 | -159.99918 | 5.070120 | -159.99918 | GoogleMaps Jarvis Island | NA | NA | NA | Pacific Ocean | 28.69200 | 28.6440 | 0.0791370 | 1 | 4 | 28.92367 | 28.930 | 0.1575958 | spr | 1 | winter | NA | NA | NA | 0.15000 | 9 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 3.00 | 75.0000 | Materials and Methods p214 | NA | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | “other” category marked as unknown | 0.6857300 | 301.84 | 23.389924 |
| 479 | EI0488 | CD073 | SI138 | 0.0400000 | % | 0.01 | Table 1 | 2016 | Jan-Apr | Jan-Apr | Materials and Methods p212 | Palmyra Atoll | Materials and Methods p212 | Western Pacific | Micronesia | 5.890000 | -162.07848 | 5.890000 | -162.07848 | GoogleMaps Palmyra Atoll | NA | NA | NA | Pacific Ocean | 28.69475 | 28.5955 | 0.1223614 | 1 | 4 | 29.05033 | 29.083 | 0.1271859 | spr | 1 | winter | NA | NA | NA | 0.15000 | 13 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 3.00 | 75.0000 | Materials and Methods p214 | NA | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | “other” category marked as unknown | 0.7907867 | 302.10 | 5.595706 |
| 480 | EI0489 | CD073 | SI139 | 0.0400000 | % | 0.01 | Table 1 | 2016 | Jan-Apr | Jan-Apr | Materials and Methods p212 | Kingman Reef | Materials and Methods p212 | Western Pacific | Micronesia | 6.487120 | -162.41682 | 6.487120 | -162.41682 | GoogleMaps Kingman Reef | NA | NA | NA | Pacific Ocean | 28.48225 | 28.3830 | 0.1399251 | 1 | 4 | 29.01033 | 28.990 | 0.0191398 | spr | 1 | winter | NA | NA | NA | 0.15000 | 14 | Materials and Methods p212 | NA | 1 | NA | Belt | 2 | 25.0000 | 3.00 | 75.0000 | Materials and Methods p214 | NA | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4168015 | 302.13 | 1.187139 |
| 481 | EI0490 | CD074 | SI140 | 17.0909100 | % | 2 | Figure 2 | 2012 | Jun | Jun | Figure 2 | Pickles Reef, Upper Florida Keys | Materials and Methods Study site and experimental nutrient treatments p545 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.001389 | -80.41528 | 25.001389 | -80.41528 | Materials and Methods Study site and experimental nutrient treatments p545, GoogleMaps | 28.13000 | Discussion Nutrient-induced bleaching p552 | Prevalence extracted using MetaDigitise in Rstudio, n = 5 | Atlantic Ocean | 27.81800 | 27.8180 | NA | 6 | 6 | 28.84867 | 29.085 | 0.9351722 | sum | 6 | summer | 4.4721360 | 0.44 | NA | 0.39500 | 1 | Materials and Methods Study site and experimental nutrient treatments p545 | 455 | 0 | NA | Circle | 5 | 5.0000 | NA | 79.0000 | Materials and Methods Disease surveys p546 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | DSS main disease found, also noted BBD; most likely others present as well, but only these mentioned; effect size is overall prevalence of disease | 0.7510910 | 302.76 | 7.185701 |
| 482 | EI0491 | CD074 | SI140 | 21.0909100 | % | 7.272727 | Figure 2 | 2012 | Jun | Jun | Figure 2 | Pickles Reef, Upper Florida Keys | Materials and Methods Study site and experimental nutrient treatments p545 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.001389 | -80.41528 | 25.001389 | -80.41528 | Materials and Methods Study site and experimental nutrient treatments p545, GoogleMaps | 28.13000 | Discussion Nutrient-induced bleaching p552 | Prevalence extracted using MetaDigitise in Rstudio, n = 4 | Atlantic Ocean | 27.81800 | 27.8180 | NA | 6 | 6 | 28.84867 | 29.085 | 0.9351722 | sum | 6 | summer | 14.5454550 | 0.44 | NA | 0.31600 | 1 | Materials and Methods Study site and experimental nutrient treatments p545 | 370 | 0 | NA | Circle | 4 | 5.0000 | NA | 79.0000 | Materials and Methods Disease surveys p546 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | DSS main disease found, also noted BBD; most likely others present as well, but only these mentioned; effect size is overall prevalence of disease | 0.7510910 | 302.76 | 7.185701 |
| 483 | EI0492 | CD074 | SI140 | 14.0000000 | % | 3.090909 | Figure 2 | 2013 | Feb | Feb | Figure 2 | Pickles Reef, Upper Florida Keys | Materials and Methods Study site and experimental nutrient treatments p545 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.001389 | -80.41528 | 25.001389 | -80.41528 | Materials and Methods Study site and experimental nutrient treatments p545, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 4 | Atlantic Ocean | 24.03000 | 24.0300 | NA | 2 | 2 | 28.38267 | 28.420 | 0.8066489 | win | 2 | winter | 6.1818180 | NA | NA | 0.31600 | 1 | Materials and Methods Study site and experimental nutrient treatments p545 | 370 | 0 | NA | Circle | 4 | 5.0000 | NA | 79.0000 | Materials and Methods Disease surveys p546 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | DSS main disease found, also noted BBD; most likely others present as well, but only these mentioned; effect size is overall prevalence of disease | 0.5842896 | 302.76 | 0.000000 |
| 484 | EI0493 | CD074 | SI140 | 28.3636400 | % | 4 | Figure 2 | 2013 | Jun | Jun | Figure 2 | Pickles Reef, Upper Florida Keys | Materials and Methods Study site and experimental nutrient treatments p545 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 25.001389 | -80.41528 | 25.001389 | -80.41528 | Materials and Methods Study site and experimental nutrient treatments p545, GoogleMaps | 27.79000 | Discussion Nutrient-induced bleaching p552 | Prevalence extracted using MetaDigitise in Rstudio, n = 4 | Atlantic Ocean | 27.55800 | 27.5580 | NA | 6 | 6 | 28.38267 | 28.420 | 0.8066489 | sum | 6 | summer | 8.0000000 | 0.16 | NA | 0.31600 | 1 | Materials and Methods Study site and experimental nutrient treatments p545 | 370 | 0 | NA | Circle | 4 | 5.0000 | NA | 79.0000 | Materials and Methods Disease surveys p546 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | DSS main disease found, also noted BBD; most likely others present as well, but only these mentioned; effect size is overall prevalence of disease | 0.3082123 | 302.76 | 0.000000 |
| 485 | EI0494 | CD075 | SI141 | 0.2600000 | % | 0.11 | Table 2 | 2012 | May-Sep | May-Sep | Materials and Methods Coral monitoring surveys | Southeast Florida | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.225525 | -80.07882 | 26.225525 | -80.07882 | Table 1 median site, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.42940 | 29.0630 | 1.2843025 | 5 | 9 | 28.78800 | 29.063 | 0.9672772 | multi | 5 | spring | NA | NA | NA | 1.40800 | 16 | Materials and Methods Coral monitoring surveys | NA | 1 | NA | Belt | 64 | 22.0000 | 1.00 | 22.0000 | Materials and Mtehods Coral monitoring surveys | NA | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Classified in paper as “WS” vs “Non-white syndrome” (groups BBD, YBD, WB (acroporids only), and DSS) | 0.3857117 | 302.58 | 1.062853 |
| 486 | EI0495 | CD075 | SI141 | 0.5100000 | % | 0.23 | Table 2 | 2013 | May-Sep | May-Sep | Materials and Methods Coral monitoring surveys | Southeast Florida | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.225525 | -80.07882 | 26.225525 | -80.07882 | Table 1 median site, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.06760 | 28.2730 | 1.3560471 | 5 | 9 | 28.32433 | 28.273 | 0.8062260 | multi | 5 | spring | NA | NA | NA | 1.93600 | 22 | Materials and Methods Coral monitoring surveys | NA | 1 | NA | Belt | 88 | 22.0000 | 1.00 | 22.0000 | Materials and Mtehods Coral monitoring surveys | NA | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Classified in paper as “WS” vs “Non-white syndrome” (groups BBD, YBD, WB (acroporids only), and DSS) | 0.7617950 | 302.58 | 0.000000 |
| 487 | EI0496 | CD075 | SI141 | 1.2400000 | % | 0.34 | Table 2 | 2014 | May-Sep | May-Sep | Materials and Methods Coral monitoring surveys | Southeast Florida | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.225525 | -80.07882 | 26.225525 | -80.07882 | Table 1 median site, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.68480 | 29.4980 | 1.4043619 | 5 | 9 | 29.15867 | 29.498 | 1.0701410 | multi | 5 | spring | NA | NA | NA | 1.93600 | 22 | Materials and Methods Coral monitoring surveys | NA | 1 | NA | Belt | 88 | 22.0000 | 1.00 | 22.0000 | Materials and Mtehods Coral monitoring surveys | NA | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Classified in paper as “WS” vs “Non-white syndrome” (groups BBD, YBD, WB (acroporids only), and DSS) | 0.2692871 | 302.58 | 0.000000 |
| 488 | EI0497 | CD075 | SI141 | 1.4900000 | % | 0.35 | Table 2 | 2015 | May-Sep | May-Sep | Materials and Methods Coral monitoring surveys | Southeast Florida | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.225525 | -80.07882 | 26.225525 | -80.07882 | Table 1 median site, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.10980 | 29.4880 | 0.8509532 | 5 | 9 | 29.43200 | 29.488 | 0.4436586 | multi | 5 | spring | NA | NA | NA | 1.93600 | 22 | Materials and Methods Coral monitoring surveys | NA | 1 | NA | Belt | 88 | 22.0000 | 1.00 | 22.0000 | Materials and Mtehods Coral monitoring surveys | NA | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Classified in paper as “WS” vs “Non-white syndrome” (groups BBD, YBD, WB (acroporids only), and DSS) | 0.8671570 | 302.58 | 2.194280 |
| 489 | EI0498 | CD075 | SI141 | 3.2900000 | % | 0.6 | Table 2 | 2016 | May-Sep | May-Sep | Materials and Methods Coral monitoring surveys | Southeast Florida | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 26.225525 | -80.07882 | 26.225525 | -80.07882 | Table 1 median site, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.04580 | 30.0950 | 1.3456276 | 5 | 9 | 29.55100 | 30.095 | 0.8223307 | multi | 5 | spring | NA | NA | NA | 1.93600 | 22 | Materials and Methods Coral monitoring surveys | NA | 1 | NA | Belt | 88 | 22.0000 | 1.00 | 22.0000 | Materials and Mtehods Coral monitoring surveys | NA | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Classified in paper as “WS” vs “Non-white syndrome” (groups BBD, YBD, WB (acroporids only), and DSS) | 0.4435806 | 302.58 | 0.000000 |
| 490 | EI0499 | CD076 | SI142 | 5.7000000 | % | 0.8 | Results p26 | 2002 | 0 | 0 | Results p26 | Akumal, Mexico | Materials and Methods p24 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 20.607490 | -87.34901 | 20.394070 | -87.31370 | GoogleMaps Akumal Mexico | NA | NA | NA | Atlantic Ocean | 29.07300 | 29.0730 | NA | 7 | 7 | 29.11933 | 29.073 | 0.3895717 | sum | 7 | summer | NA | NA | NA | 1.50000 | 10 | Materials and Methods p24 | NA | 1 | NA | Belt | 30 | 25.0000 | 2.00 | 50.0000 | Materials and Methods p24 | NA | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1728516 | 301.86 | 0.000000 |
| 491 | EI0500 | CD076 | SI142 | 7.9600000 | % | 0.7 | Results p26 | 2004 | 0 | 0 | Results p26 | Akumal, Mexico | Materials and Methods p24 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 20.607490 | -87.34901 | 20.394070 | -87.31370 | GoogleMaps Akumal Mexico | NA | NA | NA | Atlantic Ocean | 28.88800 | 28.8880 | NA | 7 | 7 | 28.89033 | 28.888 | 0.3115062 | sum | 7 | summer | NA | NA | NA | 1.50000 | 10 | Materials and Methods p24 | NA | 1 | NA | Belt | 30 | 25.0000 | 2.00 | 50.0000 | Materials and Methods p24 | NA | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3696365 | 301.86 | 0.000000 |
| 492 | EI0501 | CD077 | SI143 | 9.7000000 | % | NA | Table 2 | 2010 | Sep | Sep | Materials and Methods p164 | Zamami, Ryukyu Archipelago, Japan | Table 2 | Western Pacific | Southeast Asia | 26.201500 | 127.32083 | 26.201500 | 127.32083 | Materials and Method p164 first coordinates, GoogleMaps | NA | NA | NA | Pacific Ocean | 29.05300 | 29.0530 | NA | 9 | 9 | 28.34200 | 29.003 | 1.5789252 | aut | 9 | fall | 7.9000000 | NA | NA | 0.60000 | 2 | Materials and Methods p164 | NA | 1 | NA | Belt | 6 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p164 | NA | 5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | “Compromised health” categorized as unknown | 0.5392838 | 301.63 | 1.009985 |
| 493 | EI0502 | CD077 | SI144 | 3.6000000 | % | NA | Table 2 | 2010 | Sep | Sep | Materials and Methods p164 | Ooyama, Ryukyu Archipelago, Japan | Table 2 | Western Pacific | Southeast Asia | 26.298500 | 127.72167 | 26.298500 | 127.72167 | Materials and Method p164 first coordinates, GoogleMaps | NA | NA | NA | Pacific Ocean | 29.05300 | 29.0530 | NA | 9 | 9 | 28.34200 | 29.003 | 1.5789252 | aut | 9 | fall | 4.6000000 | NA | NA | 0.60000 | 2 | Materials and Methods p164 | NA | 1 | NA | Belt | 6 | 50.0000 | 2.00 | 100.0000 | Materials and Methods p164 | NA | 5 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9203339 | 301.72 | 1.065706 |
| 494 | EI0503 | CD078 | SI145 | 2.1578950 | % | 0.5789474 | Figure 2 | 2016 | Nov-Jan | Nov-Jan | Methods Sampling location and data collection | Southern Eleuthera, The Bahamas | Methods Sampling location and data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.749246 | -76.26184 | 24.749246 | -76.26184 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 33 | Atlantic Ocean | 26.41600 | 26.4900 | 0.8583956 | 11 | 1 | 29.33334 | 29.635 | 0.5841733 | aut | 11 | fall | 3.3257990 | NA | NA | 0.33000 | 5 | Methods Sampling location and data collection | 1232 | 1 | NA | Belt | 33 | 10.0000 | 1.00 | 10.0000 | Methods Sampling location and data collection | NA | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8839569 | 302.30 | 3.377132 |
| 495 | EI0504 | CD079 | SI146 | 20.5000000 | % | 0.7 | Results 3.1. Spatial patterns of P. lobata growth anomalies and coral cover | 2013 | Jun-Jul | Jun-Jul | Methods 2.3. Enterococci assays | Puako region, Hawaii | Methods 2.1. The Puako region and study sites | Western Pacific | Polynesia | 19.951950 | -155.87206 | 19.951950 | -155.87206 | GoogleMaps Puako, HI | NA | NA | NA | Pacific Ocean | 25.57550 | 25.5755 | 0.3429459 | 6 | 7 | 25.77700 | 25.818 | 0.4249850 | sum | 6 | summer | NA | NA | NA | 0.45000 | 10 | Methods 2.2. Coral cover and disease surveys | NA | 0 | NA | Belt | 30 | 15.0000 | 1.00 | 15.0000 | Methods 2.2. Coral cover and disease surveys | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “Porites lobata growth anomalies” categorized as GA | 0.1414337 | 300.37 | 0.000000 |
| 496 | EI0505 | CD081 | SI147 | 4.3478260 | % | 2.839988 | Figure 4 | 2008 | Oct | Oct | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | 29.54000 | Table 3 | Prevalence extracted using MetaDigitise in Rstudio, n = 6; coordinates not found in SST database, reselected nearby coordinates using GoogleMaps | Atlantic Ocean | 29.35800 | 29.3580 | NA | 10 | 10 | 27.79434 | 27.610 | 0.6097677 | aut | 10 | fall | 6.9565220 | NA | 0.3400 | 0.06000 | 1 | Figure 1 | 35 | 1 | NA | Belt | 6 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2342834 | 301.32 | 7.221392 |
| 497 | EI0506 | CD081 | SI147 | 5.0000000 | % | 4.891304 | Figure 4 | 2010 | Feb | Feb | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | 27.00000 | Table 3 | Prevalence extracted using MetaDigitise in Rstudio, n = 4; coordinates not found in SST database, reselected nearby coordinates using GoogleMaps | Atlantic Ocean | 27.04000 | 27.0400 | NA | 2 | 2 | 29.05633 | 28.853 | 0.3265474 | win | 2 | winter | 9.7826090 | NA | 0.5600 | 0.04000 | 1 | Figure 1 | 18 | 1 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1699982 | 301.32 | 0.000000 |
| 498 | EI0507 | CD081 | SI147 | 16.0869570 | % | 5.89367 | Figure 4 | 2010 | Sep | Sep | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | 29.51000 | Table 3 | Prevalence extracted using MetaDigitise in Rstudio, n = 15; coordinates not found in SST database, reselected nearby coodinatesusing GoogleMaps | Atlantic Ocean | 29.81500 | 29.8150 | NA | 9 | 9 | 29.05633 | 28.853 | 0.3265474 | aut | 9 | fall | 22.8260870 | NA | 0.3500 | 0.15000 | 1 | Figure 1 | 107 | 1 | NA | Belt | 15 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3571167 | 301.32 | 4.492830 |
| 499 | EI0508 | CD081 | SI147 | 14.5652170 | % | 4.125119 | Figure 4 | 2012 | Sep | Sep | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | 29.02000 | Table 3 | Prevalence extracted using MetaDigitise in Rstudio, n = 14; coordinates not found in SST database, reselected nearby coordinates using GoogleMaps | Atlantic Ocean | 28.99500 | 28.9950 | NA | 9 | 9 | 28.00767 | 27.875 | 0.1977904 | aut | 9 | fall | 15.4347830 | NA | 0.4300 | 0.14000 | 1 | Figure 1 | 185 | 1 | NA | Belt | 14 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.0907135 | 301.32 | 0.000000 |
| 500 | EI0509 | CD081 | SI147 | 1.7391300 | % | 1.069424 | Figure 4 | 2014 | Sep | Sep | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 5; coordinates not found in SST database, reselected nearby coordinate using GoogleMaps | Atlantic Ocean | 28.46300 | 28.4630 | NA | 9 | 9 | 27.55000 | 27.445 | 0.3834378 | aut | 9 | fall | 2.3913040 | NA | NA | 0.05000 | 1 | Figure 1 | 143 | 1 | NA | Belt | 5 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2232208 | 301.32 | 1.105721 |
| 501 | EI0510 | CD081 | SI147 | 5.6521740 | % | 4.673913 | Figure 4 | 2015 | Mar | Mar | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 4; coordinates not found in SST database, reselected nearby coordinatesusing GoogleMaps | Atlantic Ocean | 26.66500 | 26.6650 | NA | 3 | 3 | 27.42200 | 27.270 | 0.3552859 | spr | 3 | spring | 9.3478260 | NA | NA | 0.04000 | 1 | Figure 1 | 137 | 1 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.0442963 | 301.32 | 0.000000 |
| 502 | EI0511 | CD081 | SI147 | 4.3478260 | % | 2.30749 | Figure 4 | 2016 | Mar | Mar | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 6; coordinates not found in SST database, reselected nearby coordinatesusing GoogleMaps | Atlantic Ocean | 26.93500 | 26.9350 | NA | 3 | 3 | 28.22700 | 28.073 | 0.4635980 | spr | 3 | spring | 5.6521740 | NA | NA | 0.06000 | 1 | Figure 1 | 118 | 1 | NA | Belt | 6 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5349884 | 301.32 | 1.092842 |
| 503 | EI0512 | CD081 | SI147 | 0.0000000 | % | 0 | Figure 4 | 2016 | Sep | Sep | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 4; coordinates not found in SST database, reselected nearby coordinatesusing GoogleMaps | Atlantic Ocean | 29.02300 | 29.0230 | NA | 9 | 9 | 28.22700 | 28.073 | 0.4635980 | aut | 9 | fall | 0.0000000 | NA | NA | 0.04000 | 1 | Figure 1 | 68 | 1 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8828735 | 301.32 | 1.092842 |
| 504 | EI0513 | CD081 | SI147 | 1.5217390 | % | 1.195652 | Figure 4 | 2017 | Feb | Feb | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 4; coordinates not found in SST database, reselected nearby coordinatesusing GoogleMaps | Atlantic Ocean | 26.92300 | 26.9230 | NA | 2 | 2 | 28.33867 | 28.058 | 0.5416056 | win | 2 | winter | 2.3913040 | NA | NA | 0.04000 | 1 | Figure 1 | 77 | 1 | NA | Belt | 4 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4785995 | 301.32 | 6.079996 |
| 505 | EI0514 | CD081 | SI147 | 6.3043480 | % | 1.278206 | Figure 4 | 2017 | Sep-Oct | Sep-Oct | Table 2 | Playa Lechi, Kralendijk, Bonaire | Materials and methods Study site p3 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 12.160167 | -68.28203 | 12.159270 | -68.34449 | Materials and methods Study site p3, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 14; coordinates not found in SST database, reselected nearby coordinates using GoogleMaps | Atlantic Ocean | 29.21150 | 29.2115 | 0.1081873 | 9 | 10 | 28.33867 | 28.058 | 0.5416056 | aut | 9 | fall | 4.7826090 | NA | NA | 0.14000 | 1 | Figure 1 | 527 | 1 | NA | Belt | 14 | 10.0000 | 1.00 | 10.0000 | Table 2, Materials and Methods Disease prevalence and coral mortality p3, Fall 2017 data collection p4 | NA | 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2028656 | 301.32 | 6.079996 |
| 506 | EI0515 | CD082 | SI148 | 2.7027030 | % | 0.6756757 | Figure 4 | 2003 | 0 | 0 | Materials and Methods Methods p223 | Enrique, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | Materials and Methods Study area p222 | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.06800 | 28.0680 | NA | 7 | 7 | 28.15633 | 28.068 | 0.3851728 | sum | 7 | summer | 2.7027030 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.4235764 | 301.93 | 0.000000 |
| 507 | EI0516 | CD082 | SI148 | 1.0810810 | % | 0.2702703 | Figure 4 | 2004 | 0 | 0 | Materials and Methods Methods p223 | Enrique, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.15500 | 28.1550 | NA | 7 | 7 | 28.20100 | 28.155 | 0.3810876 | sum | 7 | summer | 1.0810810 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.1696777 | 301.93 | 0.000000 |
| 508 | EI0517 | CD082 | SI148 | 8.2432430 | % | 1.4864865 | Figure 4 | 2005 | 0 | 0 | Materials and Methods Methods p223 | Enrique, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.90800 | 28.9080 | NA | 7 | 7 | 28.94867 | 28.908 | 0.3080198 | sum | 7 | summer | 5.9459460 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.6728439 | 301.93 | 2.175707 |
| 509 | EI0518 | CD082 | SI148 | 16.0810810 | % | 1.4864865 | Figure 4 | 2006 | 0 | 0 | Materials and Methods Methods p223 | Enrique, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.49300 | 28.4930 | NA | 7 | 7 | 28.57100 | 28.493 | 0.1465026 | sum | 7 | summer | 5.9459460 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 1.3771362 | 301.93 | 9.668563 |
| 510 | EI0519 | CD082 | SI148 | 4.7297300 | % | 0.4054054 | Figure 4 | 2007 | 0 | 0 | Materials and Methods Methods p223 | Enrique, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.944300 | -67.03688 | 17.944300 | -67.03688 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.94500 | 28.9450 | NA | 7 | 7 | 28.89000 | 28.945 | 0.1934555 | sum | 7 | summer | 1.6216220 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.3389282 | 301.93 | 2.125688 |
| 511 | EI0520 | CD082 | SI149 | 2.5675680 | % | 0.6756757 | Figure 4 | 2003 | 0 | 0 | Materials and Methods Methods p223 | Pelotas, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.06800 | 28.0680 | NA | 7 | 7 | 28.15633 | 28.068 | 0.3851728 | sum | 7 | summer | 2.7027030 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.4250031 | 301.94 | 0.000000 |
| 512 | EI0521 | CD082 | SI149 | 3.5135140 | % | 0.6756757 | Figure 4 | 2004 | 0 | 0 | Materials and Methods Methods p223 | Pelotas, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.15500 | 28.1550 | NA | 7 | 7 | 28.20100 | 28.155 | 0.3810876 | sum | 7 | summer | 2.7027030 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.1607208 | 301.94 | 1.107150 |
| 513 | EI0522 | CD082 | SI149 | 5.8108110 | % | 0.9459459 | Figure 4 | 2005 | 0 | 0 | Materials and Methods Methods p223 | Pelotas, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.90800 | 28.9080 | NA | 7 | 7 | 28.94867 | 28.908 | 0.3080198 | sum | 7 | summer | 3.7837840 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.6764069 | 301.94 | 2.308539 |
| 514 | EI0523 | CD082 | SI149 | 10.6756760 | % | 1.7567568 | Figure 4 | 2006 | 0 | 0 | Materials and Methods Methods p223 | Pelotas, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.49300 | 28.4930 | NA | 7 | 7 | 28.57100 | 28.493 | 0.1465026 | sum | 7 | summer | 7.0270270 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 1.4200363 | 301.94 | 9.975699 |
| 515 | EI0524 | CD082 | SI149 | 8.1081080 | % | 1.0810811 | Figure 4 | 2007 | 0 | 0 | Materials and Methods Methods p223 | Pelotas, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.957367 | -67.06960 | 17.957367 | -67.06960 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.94500 | 28.9450 | NA | 7 | 7 | 28.89000 | 28.945 | 0.1934555 | sum | 7 | summer | 4.3243240 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.3371201 | 301.94 | 2.244269 |
| 516 | EI0525 | CD082 | SI150 | 4.4594590 | % | 0.8108108 | Figure 4 | 2003 | 0 | 0 | Materials and Methods Methods p223 | Turrumote, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.06800 | 28.0680 | NA | 7 | 7 | 28.15633 | 28.068 | 0.3851728 | sum | 7 | summer | 3.2432430 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.4235764 | 301.93 | 0.000000 |
| 517 | EI0526 | CD082 | SI150 | 7.1621620 | % | 0.9459459 | Figure 4 | 2004 | 0 | 0 | Materials and Methods Methods p223 | Turrumote, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.15500 | 28.1550 | NA | 7 | 7 | 28.20100 | 28.155 | 0.3810876 | sum | 7 | summer | 3.7837840 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.1696777 | 301.93 | 0.000000 |
| 518 | EI0527 | CD082 | SI150 | 10.8108110 | % | 2.027027 | Figure 4 | 2005 | 0 | 0 | Materials and Methods Methods p223 | Turrumote, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.90800 | 28.9080 | NA | 7 | 7 | 28.94867 | 28.908 | 0.3080198 | sum | 7 | summer | 8.1081080 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.6728439 | 301.93 | 2.175707 |
| 519 | EI0528 | CD082 | SI150 | 25.4054050 | % | 2.5675676 | Figure 4 | 2006 | 0 | 0 | Materials and Methods Methods p223 | Turrumote, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.49300 | 28.4930 | NA | 7 | 7 | 28.57100 | 28.493 | 0.1465026 | sum | 7 | summer | 10.2702700 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 1.3771362 | 301.93 | 9.668563 |
| 520 | EI0529 | CD082 | SI150 | 20.4054050 | % | 2.1621622 | Figure 4 | 2007 | 0 | 0 | Materials and Methods Methods p223 | Turrumote, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934950 | -67.01883 | 17.934950 | -67.01883 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.94500 | 28.9450 | NA | 7 | 7 | 28.89000 | 28.945 | 0.1934555 | sum | 7 | summer | 8.6486490 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.3389282 | 301.93 | 2.125688 |
| 521 | EI0530 | CD082 | SI151 | 3.3783780 | % | 0.5405405 | Figure 4 | 2003 | 0 | 0 | Materials and Methods Methods p223 | Media Luna, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.06800 | 28.0680 | NA | 7 | 7 | 28.15633 | 28.068 | 0.3851728 | sum | 7 | summer | 2.1621620 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.4235764 | 301.93 | 0.000000 |
| 522 | EI0531 | CD082 | SI151 | 3.7837840 | % | 0.5405405 | Figure 4 | 2004 | 0 | 0 | Materials and Methods Methods p223 | Media Luna, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.15500 | 28.1550 | NA | 7 | 7 | 28.20100 | 28.155 | 0.3810876 | sum | 7 | summer | 2.1621620 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.1696777 | 301.93 | 0.000000 |
| 523 | EI0532 | CD082 | SI151 | 10.5405410 | % | 1.8918919 | Figure 4 | 2005 | 0 | 0 | Materials and Methods Methods p223 | Media Luna, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.90800 | 28.9080 | NA | 7 | 7 | 28.94867 | 28.908 | 0.3080198 | sum | 7 | summer | 7.5675680 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.6728439 | 301.93 | 2.175707 |
| 524 | EI0533 | CD082 | SI151 | 20.1351350 | % | 1.8918919 | Figure 4 | 2006 | 0 | 0 | Materials and Methods Methods p223 | Media Luna, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.49300 | 28.4930 | NA | 7 | 7 | 28.57100 | 28.493 | 0.1465026 | sum | 7 | summer | 7.5675680 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 1.3771362 | 301.93 | 9.668563 |
| 525 | EI0534 | CD082 | SI151 | 12.4324320 | % | 1.0810811 | Figure 4 | 2007 | 0 | 0 | Materials and Methods Methods p223 | Media Luna, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.934883 | -67.04885 | 17.934883 | -67.04885 | NA | NA | NA | Prevalence extracted using MetaDigitise in Rstudio, n = 32 | Atlantic Ocean | 28.94500 | 28.9450 | NA | 7 | 7 | 28.89000 | 28.945 | 0.1934555 | sum | 7 | summer | 4.3243240 | NA | NA | 2.56000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.3389282 | 301.93 | 2.125688 |
| 526 | EI0535 | CD082 | SI152 | 9.2000000 | % | 0.6 | Figure 4 | 2003 | 0 | 0 | Materials and Methods Methods p223 | Weinberg, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.05300 | 28.0530 | NA | 7 | 7 | 28.13967 | 28.053 | 0.4414280 | sum | 7 | summer | 2.4000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.3725128 | 301.90 | 0.000000 |
| 527 | EI0536 | CD082 | SI152 | 2.2000000 | % | 0.2 | Figure 4 | 2004 | 0 | 0 | Materials and Methods Methods p223 | Weinberg, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.18800 | 28.1880 | NA | 7 | 7 | 28.23267 | 28.188 | 0.4167989 | sum | 7 | summer | 0.8000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.2014465 | 301.90 | 1.024287 |
| 528 | EI0537 | CD082 | SI152 | 4.4000000 | % | 0.6 | Figure 4 | 2005 | 0 | 0 | Materials and Methods Methods p223 | Weinberg, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.95800 | 28.9580 | NA | 7 | 7 | 28.99467 | 28.958 | 0.3315251 | sum | 7 | summer | 2.4000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.6257095 | 301.90 | 1.148554 |
| 529 | EI0538 | CD082 | SI152 | 11.0000000 | % | 2 | Figure 4 | 2006 | 0 | 0 | Materials and Methods Methods p223 | Weinberg, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.52000 | 28.5200 | NA | 7 | 7 | 28.60600 | 28.520 | 0.1755787 | sum | 7 | summer | 8.0000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 1.2942810 | 301.90 | 8.489988 |
| 530 | EI0539 | CD082 | SI152 | 8.8000000 | % | 2.6 | Figure 4 | 2007 | 0 | 0 | Materials and Methods Methods p223 | Weinberg, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.890483 | -66.98867 | 17.890483 | -66.98867 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.96000 | 28.9600 | NA | 7 | 7 | 28.88667 | 28.960 | 0.2098410 | sum | 7 | summer | 10.4000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.2899933 | 301.90 | 1.108576 |
| 531 | EI0540 | CD082 | SI153 | 10.4000000 | % | 0.8 | Figure 4 | 2003 | 0 | 0 | Materials and Methods Methods p223 | Buoy, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.889667 | -66.98483 | 17.889667 | -66.98483 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.05300 | 28.0530 | NA | 7 | 7 | 28.13967 | 28.053 | 0.4414280 | sum | 7 | summer | 3.2000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.3725128 | 301.90 | 0.000000 |
| 532 | EI0541 | CD082 | SI153 | 1.6000000 | % | 0.2 | Figure 4 | 2004 | 0 | 0 | Materials and Methods Methods p223 | Buoy, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.889667 | -66.98483 | 17.889667 | -66.98483 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.18800 | 28.1880 | NA | 7 | 7 | 28.23267 | 28.188 | 0.4167989 | sum | 7 | summer | 0.8000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.2014465 | 301.90 | 1.024287 |
| 533 | EI0542 | CD082 | SI153 | 5.4000000 | % | 1 | Figure 4 | 2005 | 0 | 0 | Materials and Methods Methods p223 | Buoy, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.889667 | -66.98483 | 17.889667 | -66.98483 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.95800 | 28.9580 | NA | 7 | 7 | 28.99467 | 28.958 | 0.3315251 | sum | 7 | summer | 4.0000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.6257095 | 301.90 | 1.148554 |
| 534 | EI0543 | CD082 | SI153 | 9.8000000 | % | 1.2 | Figure 4 | 2006 | 0 | 0 | Materials and Methods Methods p223 | Buoy, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.889667 | -66.98483 | 17.889667 | -66.98483 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.52000 | 28.5200 | NA | 7 | 7 | 28.60600 | 28.520 | 0.1755787 | sum | 7 | summer | 4.8000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 1.2942810 | 301.90 | 8.489988 |
| 535 | EI0544 | CD082 | SI153 | 3.4000000 | % | 0.6 | Figure 4 | 2007 | 0 | 0 | Materials and Methods Methods p223 | Buoy, La Parguera, Puerto Rico | Materials and Methods Study area p222 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.889667 | -66.98483 | 17.889667 | -66.98483 | NA | NA | NA | Prevalence extracted using MetaDigitise in R, n = 32 | Atlantic Ocean | 28.96000 | 28.9600 | NA | 7 | 7 | 28.88667 | 28.960 | 0.2098410 | sum | 7 | summer | 2.4000000 | NA | NA | 0.32000 | 4 | Materials and Methods Methods p223 | NA | 1 | Depth intervals considered different sites | Belt | 32 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Methods p223 | NA | 10 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | “Caribbean white syndromes” and “White plague disease” grouped under WS | 0.2899933 | 301.90 | 1.108576 |
| 536 | EI0545 | CD083 | SI154 | 0.0000000 | % | 0 | Figure 6b | 2007 | Oct | Oct | Figure 6b | Atol das Rocas, Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -3.850000 | -33.81667 | -3.850000 | -33.81667 | Methods Coral dataset p443 | NA | NA | Prevalence extracted using MetaDigitise in R, n = 54 | Atlantic Ocean | 26.64500 | 26.6450 | NA | 10 | 10 | 27.64433 | 27.570 | 0.3445668 | spr | 4 | spring | 0.0000000 | NA | NA | 0.54000 | 9 | Table 1 | NA | 1 | NA | Belt | 54 | 20.0000 | 0.50 | 10.0000 | Methods Coral dataset p444 | didn’t specify transect number so took avg of 4-8 and then multiplied by 9 sites | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1875076 | 301.40 | 0.000000 |
| 537 | EI0546 | CD083 | SI154 | 6.8571430 | % | 1.224832 | Figure 6b | 2010 | Mar | Mar | Figure 6b | Atol das Rocas, Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -3.850000 | -33.81667 | -3.850000 | -33.81667 | Methods Coral dataset p443 | NA | NA | Prevalence extracted using MetaDigitise in R, n = 18 | Atlantic Ocean | 29.02800 | 29.0280 | NA | 3 | 3 | 27.89433 | 27.953 | 0.1870332 | aut | 9 | fall | 5.1965230 | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 20.0000 | 0.50 | 10.0000 | Methods Coral dataset p444 | didn’t specify transect number so took avg of 4-8 and then multiplied by 3 sites | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5971375 | 301.40 | 4.049971 |
| 538 | EI0547 | CD083 | SI154 | 29.8571430 | % | 2.763285 | Figure 6b | 2010 | Dec | Dec | Figure 6b | Atol das Rocas, Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -3.850000 | -33.81667 | -3.850000 | -33.81667 | Methods Coral dataset p443 | NA | NA | Prevalence extracted using MetaDigitise in R, n = 54 | Atlantic Ocean | 27.68500 | 27.6850 | NA | 12 | 12 | 27.89433 | 27.953 | 0.1870332 | sum | 6 | summer | 20.3059170 | NA | NA | 0.54000 | 9 | Table 1 | NA | 1 | NA | Belt | 54 | 20.0000 | 0.50 | 10.0000 | Methods Coral dataset p444 | didn’t specify transect number so took avg of 4-8 and then multiplied by 9 sites | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2421570 | 301.40 | 7.682823 |
| 539 | EI0548 | CD083 | SI155 | 1.6549300 | % | 0.3358438 | Figure 6d | 2008 | Sep | Sep | Figure 6d | Fernando de Noronha, Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -3.850000 | -32.41667 | -3.850000 | -32.41667 | Methods Coral dataset p443 | NA | NA | Prevalence extracted using MetaDigitise in R, n = 30 | Atlantic Ocean | 26.83500 | 26.8350 | NA | 9 | 9 | 27.71033 | 27.718 | 0.2385930 | spr | 3 | spring | 1.8394920 | NA | NA | 0.30000 | 5 | Table 1 | NA | 1 | NA | Belt | 30 | 20.0000 | 0.50 | 10.0000 | Methods Coral dataset p444 | didn’t specify transect number so took avg of 4-8 and then multiplied by 5 sites | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4142838 | 301.46 | 0.000000 |
| 540 | EI0549 | CD083 | SI155 | 1.1619720 | % | 0.2746776 | Figure 6d | 2009 | Nov | Nov | Figure 6d | Fernando de Noronha, Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -3.850000 | -32.41667 | -3.850000 | -32.41667 | Methods Coral dataset p443 | NA | NA | Prevalence extracted using MetaDigitise in R, n = 30 | Atlantic Ocean | 26.95500 | 26.9550 | NA | 11 | 11 | 27.74100 | 27.773 | 0.4758071 | spr | 5 | spring | 1.5044710 | NA | NA | 0.30000 | 5 | Table 1 | NA | 1 | NA | Belt | 30 | 20.0000 | 0.50 | 10.0000 | Methods Coral dataset p444 | didn’t specify transect number so took avg of 4-8 and then multiplied by 5 sites | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6228943 | 301.46 | 4.784301 |
| 541 | EI0550 | CD083 | SI155 | 12.2711270 | % | 2.5528396 | Figure 6d | 2010 | Nov | Nov | Figure 6d | Fernando de Noronha, Brazil | Figure 1 | XXXX | Caribbean/Atlantic | -3.850000 | -32.41667 | -3.850000 | -32.41667 | Methods Coral dataset p443 | NA | NA | Prevalence extracted using MetaDigitise in R, n = 24 | Atlantic Ocean | 27.52000 | 27.5200 | NA | 11 | 11 | 27.86033 | 27.890 | 0.1991643 | spr | 5 | spring | 12.5063090 | NA | NA | 0.24000 | 4 | Table 1 | NA | 1 | NA | Belt | 24 | 20.0000 | 0.50 | 10.0000 | Methods Coral dataset p444 | didn’t specify transect number so took avg of 4-8 and then multiplied by 4 sites | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2571411 | 301.46 | 3.187110 |
| 542 | EI0551 | CD084 | SI156 | 3.1000000 | % | 0.6 | Results Impact of dredging on coral disease prevalence | 2011 | Dec | Dec | Methods Coral health and community composition surveys | Montebello and Barrow Islands, Western Australia | Figure 1 | Eastern Indian Ocean | Australia | -20.605990 | 115.46835 | -20.605990 | 115.46835 | GoogleMaps Montebello and Barrow Islands | NA | NA | NA | Indian Ocean | 27.63000 | 27.6300 | NA | 12 | 12 | 28.62200 | 28.938 | 0.8777522 | sum | 6 | summer | NA | NA | NA | 0.54000 | 6 | Methods Coral health and community composition surveys | NA | NA | NA | Belt | 18 | 15.0000 | 2.00 | 30.0000 | Methods Coral health and community composition surveys | NA | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5014038 | 302.07 | 1.025704 |
| 543 | EI0552 | CD084 | SI156 | 4.7000000 | % | 1.5 | Results Impact of dredging on coral disease prevalence | 2011 | Dec | Dec | Methods Coral health and community composition surveys | Montebello and Barrow Islands, Western Australia | Figure 1 | Eastern Indian Ocean | Australia | -20.605990 | 115.46835 | -20.605990 | 115.46835 | GoogleMaps Montebello and Barrow Islands | NA | NA | NA | Indian Ocean | 27.63000 | 27.6300 | NA | 12 | 12 | 28.62200 | 28.938 | 0.8777522 | sum | 6 | summer | NA | NA | NA | 0.27000 | 3 | Methods Coral health and community composition surveys | NA | NA | NA | Belt | 9 | 15.0000 | 2.00 | 30.0000 | Methods Coral health and community composition surveys | NA | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5014038 | 302.07 | 1.025704 |
| 544 | EI0553 | CD084 | SI156 | 7.2600000 | % | 1.56 | Results Impact of dredging on coral disease prevalence | 2011 | Dec | Dec | Methods Coral health and community composition surveys | Montebello and Barrow Islands, Western Australia | Figure 1 | Eastern Indian Ocean | Australia | -20.605990 | 115.46835 | -20.605990 | 115.46835 | GoogleMaps Montebello and Barrow Islands | NA | NA | NA | Indian Ocean | 27.63000 | 27.6300 | NA | 12 | 12 | 28.62200 | 28.938 | 0.8777522 | sum | 6 | summer | NA | NA | NA | 0.18000 | 2 | Methods Coral health and community composition surveys | NA | NA | NA | Belt | 6 | 15.0000 | 2.00 | 30.0000 | Methods Coral health and community composition surveys | NA | 5 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5014038 | 302.07 | 1.025704 |
| 545 | EI0554 | CD085 | SI157 | 17.0000000 | % | NA | Table 1 | 2001 | Mar | Mar | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 22.47300 | 22.4730 | NA | 3 | 3 | 27.51033 | 27.875 | 1.3669808 | spr | 3 | spring | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 1.4271240 | 301.82 | 0.000000 |
| 546 | EI0555 | CD085 | SI157 | 11.0000000 | % | NA | Table 1 | 2001 | Mar | Mar | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 22.47300 | 22.4730 | NA | 3 | 3 | 27.51033 | 27.875 | 1.3669808 | spr | 3 | spring | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 1.4271240 | 301.82 | 0.000000 |
| 547 | EI0556 | CD085 | SI157 | 3.0000000 | % | NA | Table 1 | 2001 | Mar | Mar | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 22.47300 | 22.4730 | NA | 3 | 3 | 27.51033 | 27.875 | 1.3669808 | spr | 3 | spring | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 1.4271240 | 301.82 | 0.000000 |
| 548 | EI0557 | CD085 | SI157 | 21.0000000 | % | NA | Table 1 | 2001 | Aug | Aug | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 28.65800 | 28.6580 | NA | 8 | 8 | 27.51033 | 27.875 | 1.3669808 | sum | 8 | summer | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 0.8871460 | 301.82 | 2.572831 |
| 549 | EI0558 | CD085 | SI157 | 13.0000000 | % | NA | Table 1 | 2001 | Aug | Aug | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 28.65800 | 28.6580 | NA | 8 | 8 | 27.51033 | 27.875 | 1.3669808 | sum | 8 | summer | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 0.8871460 | 301.82 | 2.572831 |
| 550 | EI0559 | CD085 | SI157 | 4.0000000 | % | NA | Table 1 | 2001 | Aug | Aug | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 28.65800 | 28.6580 | NA | 8 | 8 | 27.51033 | 27.875 | 1.3669808 | sum | 8 | summer | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 0.8871460 | 301.82 | 2.572831 |
| 551 | EI0560 | CD085 | SI157 | 17.0000000 | % | NA | Table 1 | 2002 | Mar | Mar | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 22.38300 | 22.3830 | NA | 3 | 3 | 27.13867 | 27.618 | 1.2282738 | spr | 3 | spring | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 1.5621414 | 301.82 | 2.572831 |
| 552 | EI0561 | CD085 | SI157 | 10.0000000 | % | NA | Table 1 | 2002 | Mar | Mar | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 22.38300 | 22.3830 | NA | 3 | 3 | 27.13867 | 27.618 | 1.2282738 | spr | 3 | spring | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 1.5621414 | 301.82 | 2.572831 |
| 553 | EI0562 | CD085 | SI157 | 3.0000000 | % | NA | Table 1 | 2002 | Mar | Mar | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 22.38300 | 22.3830 | NA | 3 | 3 | 27.13867 | 27.618 | 1.2282738 | spr | 3 | spring | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 1.5621414 | 301.82 | 2.572831 |
| 554 | EI0563 | CD085 | SI157 | 22.0000000 | % | NA | Table 1 | 2002 | Aug | Aug | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 28.05500 | 28.0550 | NA | 8 | 8 | 27.13867 | 27.618 | 1.2282738 | sum | 8 | summer | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 0.8382416 | 301.82 | 1.000008 |
| 555 | EI0564 | CD085 | SI157 | 8.0000000 | % | NA | Table 1 | 2002 | Aug | Aug | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 28.05500 | 28.0550 | NA | 8 | 8 | 27.13867 | 27.618 | 1.2282738 | sum | 8 | summer | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 0.8382416 | 301.82 | 1.000008 |
| 556 | EI0565 | CD085 | SI157 | 1.0000000 | % | NA | Table 1 | 2002 | Aug | Aug | Table 1 | Gulf of Eilat, Red Sea | Material and Methods Field censuses | Western Indian Ocean | Middle East | 29.501210 | 34.91748 | 27.680610 | 34.60500 | GoogleMaps | NA | NA | NA | Indian Ocean | 28.05500 | 28.0550 | NA | 8 | 8 | 27.13867 | 27.618 | 1.2282738 | sum | 8 | summer | NA | NA | NA | 0.18000 | 3 | Table 1 | NA | 1 | NA | Belt | 18 | 10.0000 | 1.00 | 10.0000 | Material and Methods Field censuses | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | NA | 0.8382416 | 301.82 | 1.000008 |
| 557 | EI0566 | CD086 | SI158 | 5.3953490 | % | 1.1390603 | Figure 6b | 2002 | Jun | Jun | Methods AGRRA surveys and disease monitoring p124 | Coral City, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 28.63800 | 28.6380 | NA | 6 | 6 | 29.33367 | 29.323 | 0.7010611 | sum | 6 | summer | 1.1390603 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2564392 | 302.62 | 0.000000 |
| 558 | EI0567 | CD086 | SI158 | 0.0000000 | % | 0 | Figure 6b | 2004 | Feb | Feb | Methods AGRRA surveys and disease monitoring p124 | Coral City, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 26.89800 | 26.8980 | NA | 2 | 2 | 29.21867 | 29.290 | 0.5286226 | win | 2 | winter | 0.0000000 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6146469 | 302.62 | 0.000000 |
| 559 | EI0568 | CD086 | SI158 | 4.1860470 | % | 0.616991 | Figure 6b | 2002 | Jun | Jun | Methods AGRRA surveys and disease monitoring p124 | Grundy’s Gardens, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 28.63800 | 28.6380 | NA | 6 | 6 | 29.33367 | 29.323 | 0.7010611 | sum | 6 | summer | 0.6169910 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2564392 | 302.62 | 0.000000 |
| 560 | EI0569 | CD086 | SI158 | 0.0000000 | % | 0 | Figure 6b | 2004 | Feb | Feb | Methods AGRRA surveys and disease monitoring p124 | Grundy’s Gardens, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 26.89800 | 26.8980 | NA | 2 | 2 | 29.21867 | 29.290 | 0.5286226 | win | 2 | winter | 0.0000000 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6146469 | 302.62 | 0.000000 |
| 561 | EI0570 | CD086 | SI158 | 3.9069770 | % | 1.4475558 | Figure 6b | 2002 | Jun | Jun | Methods AGRRA surveys and disease monitoring p124 | Jigsaw Puzzle, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 28.63800 | 28.6380 | NA | 6 | 6 | 29.33367 | 29.323 | 0.7010611 | sum | 6 | summer | 1.4475558 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2564392 | 302.62 | 0.000000 |
| 562 | EI0571 | CD086 | SI158 | 1.1627910 | % | 0.3796868 | Figure 6b | 2004 | Feb | Feb | Methods AGRRA surveys and disease monitoring p124 | Jigsaw Puzzle, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 26.89800 | 26.8980 | NA | 2 | 2 | 29.21867 | 29.290 | 0.5286226 | win | 2 | winter | 0.3796868 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6146469 | 302.62 | 0.000000 |
| 563 | EI0572 | CD086 | SI158 | 5.5813950 | % | 0.8542952 | Figure 6b | 2002 | Jun | Jun | Methods AGRRA surveys and disease monitoring p124 | Sailfin, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 28.63800 | 28.6380 | NA | 6 | 6 | 29.33367 | 29.323 | 0.7010611 | sum | 6 | summer | 0.8542952 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2564392 | 302.62 | 0.000000 |
| 564 | EI0573 | CD086 | SI158 | 0.7441860 | % | 0.403172 | Figure 6b | 2004 | Feb | Feb | Methods AGRRA surveys and disease monitoring p124 | Sailfin, Little Cayman, Cayman Islands | Methods Measuring in the field Study site p124 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 19.698120 | -80.03659 | 19.698120 | -80.03659 | GoogleMaps Little Cayman | NA | NA | Prevalence extracted using MetaDigitise in RStudio, n = | Atlantic Ocean | 26.89800 | 26.8980 | NA | 2 | 2 | 29.21867 | 29.290 | 0.5286226 | win | 2 | winter | 0.4031720 | NA | NA | 0.01000 | 1 | Figure 6b | NA | 1 | NA | Line | 1 | 10.0000 | 1.00 | 10.0000 | Methods AGRRA surveys and disease monitoring p125 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6146469 | 302.62 | 0.000000 |
| 565 | EI0574 | CD087 | SI159 | 49.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Diploastrea | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 566 | EI0575 | CD087 | SI159 | 19.6000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Fungia | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 567 | EI0576 | CD087 | SI159 | 14.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Diploastrea | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 568 | EI0577 | CD087 | SI159 | 32.2000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Fungia | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 569 | EI0578 | CD087 | SI159 | 15.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Diploastrea | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 570 | EI0579 | CD087 | SI159 | 30.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Fungia | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 571 | EI0580 | CD087 | SI159 | 3.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Diploastrea | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 572 | EI0581 | CD087 | SI159 | 26.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Fungia | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 573 | EI0582 | CD087 | SI159 | 17.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Diploastrea | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 574 | EI0583 | CD087 | SI159 | 26.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Fungia | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 575 | EI0584 | CD087 | SI159 | 8.3000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Diploastrea | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 576 | EI0585 | CD087 | SI159 | 24.0000000 | % | NA | Table 3 | 2004 | Aug | Aug | Materials and Methods | Wakatobi Island Chain | Materials and Methods | Coral Triangle & SE Asia | Southeast Asia | -5.546940 | 123.93089 | -5.546940 | 123.93089 | GoogleMaps Wakatobi National Park | NA | NA | Fungia | Pacific Ocean | 26.87500 | 26.8750 | NA | 8 | 8 | 29.67533 | 29.453 | 0.4816597 | win | 2 | winter | NA | NA | NA | 0.07500 | 1 | Table 3 | NA | 0 | NA | Belt | 5 | 15.0000 | 1.00 | 15.0000 | Materials and Methods | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4807205 | 302.43 | 2.644274 |
| 577 | EI0586 | CD088 | SI160 | 13.7000000 | % | 0.82 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 1 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 578 | EI0587 | CD088 | SI160 | 9.5000000 | % | 0.9 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 1 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 579 | EI0588 | CD088 | SI160 | 0.6500000 | % | 7.00E-02 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 1 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 580 | EI0589 | CD088 | SI160 | 0.2200000 | % | 0.04 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 1 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 581 | EI0590 | CD088 | SI160 | 2.2000000 | % | 0.44 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 1 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 582 | EI0591 | CD088 | SI160 | 2.9000000 | % | 0.96 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 0 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 583 | EI0592 | CD088 | SI160 | 0.1400000 | % | 0.14 | Table 1 | 2011 | Jan-Feb | Jan-Feb | Table 1 | Western Hawai’i | Figure 1 | Western Pacific | Polynesia | 19.571080 | -155.96475 | 19.571080 | -155.96475 | GoogleMaps Keauhou Bay, HI | NA | NA | NA | Pacific Ocean | 24.71250 | 24.7125 | 0.1237431 | 1 | 2 | 25.12933 | 25.055 | 0.3034082 | win | 1 | winter | NA | NA | NA | 0.72000 | 9 | Figure 1 | NA | 1 | NA | Belt | 36 | 10.0000 | 2.00 | 20.0000 | Methods Coral health assessments p3 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4599915 | 300.38 | 0.000000 |
| 585 | EI0594 | CD091 | SI162 | 12.2058820 | % | 1.7647059 | Figure 4 | 1997 | Apr | Apr | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 26.66500 | 26.6650 | NA | 4 | 4 | 27.71533 | 27.453 | 0.2275882 | spr | 4 | spring | 5.2941180 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3542786 | 301.47 | 1.048555 |
| 586 | EI0595 | CD091 | SI163 | 7.5000000 | % | 1.0294118 | Figure 4 | 1997 | Apr | Apr | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 26.66500 | 26.6650 | NA | 4 | 4 | 27.71533 | 27.453 | 0.2275882 | spr | 4 | spring | 1.7829930 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3542786 | 301.47 | 1.048555 |
| 587 | EI0596 | CD091 | SI164 | 0.0000000 | % | 0 | Figure 4 | 1997 | Apr | Apr | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 26.66500 | 26.6650 | NA | 4 | 4 | 27.71533 | 27.453 | 0.2275882 | spr | 4 | spring | 0.0000000 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9771423 | 301.58 | 1.054278 |
| 588 | EI0597 | CD091 | SI162 | 15.0000000 | % | 4.1176471 | Figure 4 | 1997 | Jul | Jul | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 27.45300 | 27.4530 | NA | 7 | 7 | 27.71533 | 27.453 | 0.2275882 | sum | 7 | summer | 12.3529410 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8321381 | 301.47 | 1.048555 |
| 589 | EI0598 | CD091 | SI163 | 7.0588240 | % | 1.7647059 | Figure 4 | 1997 | Jul | Jul | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.45300 | 27.4530 | NA | 7 | 7 | 27.71533 | 27.453 | 0.2275882 | sum | 7 | summer | 3.0565600 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8321381 | 301.47 | 1.048555 |
| 590 | EI0599 | CD091 | SI164 | 4.7058820 | % | 0.7352941 | Figure 4 | 1997 | Jul | Jul | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.45300 | 27.4530 | NA | 7 | 7 | 27.71533 | 27.453 | 0.2275882 | sum | 7 | summer | 1.2735670 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9600067 | 301.58 | 1.054278 |
| 591 | EI0600 | CD091 | SI162 | 14.2647060 | % | 1.4705882 | Figure 4 | 1997 | Oct | Oct | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 28.64500 | 28.6450 | NA | 10 | 10 | 27.71533 | 27.453 | 0.2275882 | aut | 10 | fall | 4.4117650 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5985718 | 301.47 | 1.048555 |
| 592 | EI0601 | CD091 | SI163 | 9.2647060 | % | 2.6470588 | Figure 4 | 1997 | Oct | Oct | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.64500 | 28.6450 | NA | 10 | 10 | 27.71533 | 27.453 | 0.2275882 | aut | 10 | fall | 4.5848400 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5985718 | 301.47 | 1.048555 |
| 593 | EI0602 | CD091 | SI164 | 5.8823530 | % | 1.1764706 | Figure 4 | 1997 | Oct | Oct | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.64500 | 28.6450 | NA | 10 | 10 | 27.71533 | 27.453 | 0.2275882 | aut | 10 | fall | 2.0377070 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0742798 | 301.58 | 1.054278 |
| 594 | EI0603 | CD091 | SI162 | 11.1764710 | % | 2.5 | Figure 4 | 1997 | Dec | Dec | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 27.37800 | 27.3780 | NA | 12 | 12 | 27.71533 | 27.453 | 0.2275882 | win | 12 | winter | 7.5000000 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.8157425 | 301.47 | 0.000000 |
| 595 | EI0604 | CD091 | SI163 | 5.4411760 | % | 1.9117647 | Figure 4 | 1997 | Dec | Dec | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.37800 | 27.3780 | NA | 12 | 12 | 27.71533 | 27.453 | 0.2275882 | win | 12 | winter | 3.3112740 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.8157425 | 301.47 | 0.000000 |
| 596 | EI0605 | CD091 | SI164 | 3.3823530 | % | 1.7647059 | Figure 4 | 1997 | Dec | Dec | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.37800 | 27.3780 | NA | 12 | 12 | 27.71533 | 27.453 | 0.2275882 | win | 12 | winter | 3.0565600 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | 9398 | 1 | Coral_N aggregated for all reefs | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.6403580 | 301.58 | 0.000000 |
| 597 | EI0606 | CD091 | SI162 | 11.3235290 | % | 1.1764706 | Figure 4 | 1998 | Feb | Feb | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 26.71000 | 26.7100 | NA | 2 | 2 | 28.57300 | 28.253 | 0.3082611 | win | 2 | winter | 3.5294120 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.2138977 | 301.47 | 0.000000 |
| 598 | EI0607 | CD091 | SI163 | 3.8235290 | % | 1.3235294 | Figure 4 | 1998 | Feb | Feb | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 26.71000 | 26.7100 | NA | 2 | 2 | 28.57300 | 28.253 | 0.3082611 | win | 2 | winter | 2.2924200 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.2138977 | 301.47 | 0.000000 |
| 599 | EI0608 | CD091 | SI164 | 1.6176470 | % | 0.8823529 | Figure 4 | 1998 | Feb | Feb | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 26.71000 | 26.7100 | NA | 2 | 2 | 28.57300 | 28.253 | 0.3082611 | win | 2 | winter | 1.5282800 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 2.0314178 | 301.58 | 0.000000 |
| 600 | EI0609 | CD091 | SI162 | 16.6176470 | % | 0.8823529 | Figure 4 | 1998 | Apr | Apr | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 27.19300 | 27.1930 | NA | 4 | 4 | 28.57300 | 28.253 | 0.3082611 | spr | 4 | spring | 2.6470590 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7299805 | 301.47 | 0.000000 |
| 601 | EI0610 | CD091 | SI163 | 6.3235290 | % | 2.2058824 | Figure 4 | 1998 | Apr | Apr | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.19300 | 27.1930 | NA | 4 | 4 | 28.57300 | 28.253 | 0.3082611 | spr | 4 | spring | 3.8207000 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7299805 | 301.47 | 0.000000 |
| 602 | EI0611 | CD091 | SI164 | 3.0882350 | % | 1.3235294 | Figure 4 | 1998 | Apr | Apr | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.19300 | 27.1930 | NA | 4 | 4 | 28.57300 | 28.253 | 0.3082611 | spr | 4 | spring | 2.2924200 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6510696 | 301.58 | 0.000000 |
| 603 | EI0612 | CD091 | SI162 | 11.7647060 | % | 1.4705882 | Figure 4 | 1998 | Jun | Jun | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 28.59800 | 28.5980 | NA | 6 | 6 | 28.57300 | 28.253 | 0.3082611 | sum | 6 | summer | 4.4117650 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7299805 | 301.47 | 0.000000 |
| 604 | EI0613 | CD091 | SI163 | 5.1470590 | % | 2.6470588 | Figure 4 | 1998 | Jun | Jun | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.59800 | 28.5980 | NA | 6 | 6 | 28.57300 | 28.253 | 0.3082611 | sum | 6 | summer | 4.5848400 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7299805 | 301.47 | 0.000000 |
| 605 | EI0614 | CD091 | SI164 | 3.9705880 | % | 2.0588235 | Figure 4 | 1998 | Jun | Jun | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.59800 | 28.5980 | NA | 6 | 6 | 28.57300 | 28.253 | 0.3082611 | sum | 6 | summer | 3.5659870 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6510696 | 301.58 | 0.000000 |
| 606 | EI0615 | CD091 | SI162 | 16.6176470 | % | 3.2352941 | Figure 4 | 1998 | Aug | Aug | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 28.86800 | 28.8680 | NA | 8 | 8 | 28.57300 | 28.253 | 0.3082611 | sum | 8 | summer | 9.7058820 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1428528 | 301.47 | 0.000000 |
| 607 | EI0616 | CD091 | SI163 | 8.5294120 | % | 1.9117647 | Figure 4 | 1998 | Aug | Aug | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.86800 | 28.8680 | NA | 8 | 8 | 28.57300 | 28.253 | 0.3082611 | sum | 8 | summer | 3.3112740 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1428528 | 301.47 | 0.000000 |
| 608 | EI0617 | CD091 | SI164 | 0.0000000 | % | 0 | Figure 4 | 1998 | Aug | Aug | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.86800 | 28.8680 | NA | 8 | 8 | 28.57300 | 28.253 | 0.3082611 | sum | 8 | summer | 0.0000000 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2107086 | 301.58 | 0.000000 |
| 609 | EI0618 | CD091 | SI162 | 8.0882350 | % | 2.2058824 | Figure 4 | 1998 | Oct | Oct | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 28.93000 | 28.9300 | NA | 10 | 10 | 28.57300 | 28.253 | 0.3082611 | aut | 10 | fall | 6.6176470 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4139481 | 301.47 | 4.638586 |
| 610 | EI0619 | CD091 | SI163 | 1.4705880 | % | 1.6176471 | Figure 4 | 1998 | Oct | Oct | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.93000 | 28.9300 | NA | 10 | 10 | 28.57300 | 28.253 | 0.3082611 | aut | 10 | fall | 2.8018470 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4139481 | 301.47 | 4.638586 |
| 611 | EI0620 | CD091 | SI164 | 0.0000000 | % | 0 | Figure 4 | 1998 | Oct | Oct | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 28.93000 | 28.9300 | NA | 10 | 10 | 28.57300 | 28.253 | 0.3082611 | aut | 10 | fall | 0.0000000 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4075165 | 301.58 | 5.652842 |
| 612 | EI0621 | CD091 | SI162 | 7.7941180 | % | 0.5882353 | Figure 4 | 1998 | Dec | Dec | Figure 4 | Gayraca, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.318730 | -74.10829 | 11.318730 | -74.10829 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 27.38000 | 27.3800 | NA | 12 | 12 | 28.57300 | 28.253 | 0.3082611 | win | 12 | winter | 1.7647060 | NA | NA | 0.54000 | 3 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 9 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4139481 | 301.47 | 6.911417 |
| 613 | EI0622 | CD091 | SI163 | 3.9705880 | % | 1.9117647 | Figure 4 | 1998 | Dec | Dec | Figure 4 | Chengue, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.317340 | -74.13297 | 11.317340 | -74.13297 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.38000 | 27.3800 | NA | 12 | 12 | 28.57300 | 28.253 | 0.3082611 | win | 12 | winter | 3.3112740 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4139481 | 301.47 | 6.911417 |
| 614 | EI0623 | CD091 | SI164 | 0.0000000 | % | 0 | Figure 4 | 1998 | Dec | Dec | Figure 4 | Granate, Tayrona Natural Park, Colombia | Methods Study area p619 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 11.272050 | -74.19651 | 11.272050 | -74.19651 | Methods Study area p619, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Atlantic Ocean | 27.38000 | 27.3800 | NA | 12 | 12 | 28.57300 | 28.253 | 0.3082611 | win | 12 | winter | 0.0000000 | NA | NA | 0.18000 | 1 | Methods Sampling and data analysis p620 | NA | 1 | NA | Belt | 3 | 30.0000 | 2.00 | 60.0000 | Methods Sampling and data analysis p620 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4075165 | 301.58 | 7.907119 |
| 615 | EI0624 | CD092 | SI165 | 0.9100000 | % | NA | Table 2 | 2004 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.62033 | 27.8180 | 0.2285966 | 7 | 9 | 26.69867 | 27.370 | 1.5668571 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4249878 | 300.46 | 8.265669 |
| 616 | EI0625 | CD092 | SI165 | 0.0200000 | % | NA | Table 2 | 2004 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.62033 | 27.8180 | 0.2285966 | 7 | 9 | 26.69867 | 27.370 | 1.5668571 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4249878 | 300.46 | 8.265669 |
| 617 | EI0626 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2004 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.62033 | 27.8180 | 0.2285966 | 7 | 9 | 26.69867 | 27.370 | 1.5668571 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4249878 | 300.46 | 8.265669 |
| 618 | EI0627 | CD092 | SI165 | 0.5900000 | % | NA | Table 2 | 2004 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.62033 | 27.8180 | 0.2285966 | 7 | 9 | 26.69867 | 27.370 | 1.5668571 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4249878 | 300.46 | 8.265669 |
| 619 | EI0628 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2004 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.62033 | 27.8180 | 0.2285966 | 7 | 9 | 26.69867 | 27.370 | 1.5668571 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4249878 | 300.46 | 8.265669 |
| 620 | EI0629 | CD092 | SI165 | 0.5900000 | % | NA | Table 2 | 2005 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.50100 | 27.8650 | 0.3465663 | 7 | 9 | 26.52200 | 27.463 | 1.9881887 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7532272 | 300.46 | 2.252853 |
| 621 | EI0630 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2005 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.50100 | 27.8650 | 0.3465663 | 7 | 9 | 26.52200 | 27.463 | 1.9881887 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7532272 | 300.46 | 2.252853 |
| 622 | EI0631 | CD092 | SI165 | 0.0500000 | % | NA | Table 2 | 2005 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.50100 | 27.8650 | 0.3465663 | 7 | 9 | 26.52200 | 27.463 | 1.9881887 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7532272 | 300.46 | 2.252853 |
| 623 | EI0632 | CD092 | SI165 | 0.5000000 | % | NA | Table 2 | 2005 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.50100 | 27.8650 | 0.3465663 | 7 | 9 | 26.52200 | 27.463 | 1.9881887 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7532272 | 300.46 | 2.252853 |
| 624 | EI0633 | CD092 | SI165 | 0.0100000 | % | NA | Table 2 | 2005 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.50100 | 27.8650 | 0.3465663 | 7 | 9 | 26.52200 | 27.463 | 1.9881887 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7532272 | 300.46 | 2.252853 |
| 625 | EI0634 | CD092 | SI165 | 0.3500000 | % | NA | Table 2 | 2006 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.30267 | 27.7750 | 0.4094713 | 7 | 9 | 26.38933 | 27.048 | 1.8073755 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9100037 | 300.46 | 3.435676 |
| 626 | EI0635 | CD092 | SI165 | 0.0100000 | % | NA | Table 2 | 2006 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.30267 | 27.7750 | 0.4094713 | 7 | 9 | 26.38933 | 27.048 | 1.8073755 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9100037 | 300.46 | 3.435676 |
| 627 | EI0636 | CD092 | SI165 | 0.0900000 | % | NA | Table 2 | 2006 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.30267 | 27.7750 | 0.4094713 | 7 | 9 | 26.38933 | 27.048 | 1.8073755 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9100037 | 300.46 | 3.435676 |
| 628 | EI0637 | CD092 | SI165 | 0.2100000 | % | NA | Table 2 | 2006 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.30267 | 27.7750 | 0.4094713 | 7 | 9 | 26.38933 | 27.048 | 1.8073755 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9100037 | 300.46 | 3.435676 |
| 629 | EI0638 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2006 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.30267 | 27.7750 | 0.4094713 | 7 | 9 | 26.38933 | 27.048 | 1.8073755 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9100037 | 300.46 | 3.435676 |
| 630 | EI0639 | CD092 | SI165 | 0.2300000 | % | NA | Table 2 | 2007 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.11100 | 27.6300 | 0.6107394 | 7 | 9 | 25.74200 | 26.438 | 2.3158171 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7542877 | 300.46 | 1.007133 |
| 631 | EI0640 | CD092 | SI165 | 0.0100000 | % | NA | Table 2 | 2007 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.11100 | 27.6300 | 0.6107394 | 7 | 9 | 25.74200 | 26.438 | 2.3158171 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7542877 | 300.46 | 1.007133 |
| 632 | EI0641 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2007 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.11100 | 27.6300 | 0.6107394 | 7 | 9 | 25.74200 | 26.438 | 2.3158171 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7542877 | 300.46 | 1.007133 |
| 633 | EI0642 | CD092 | SI165 | 0.2200000 | % | NA | Table 2 | 2007 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.11100 | 27.6300 | 0.6107394 | 7 | 9 | 25.74200 | 26.438 | 2.3158171 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7542877 | 300.46 | 1.007133 |
| 634 | EI0643 | CD092 | SI165 | 0.1500000 | % | NA | Table 2 | 2008 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.67600 | 27.7180 | 0.2823523 | 7 | 9 | 26.48767 | 27.375 | 1.8419546 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7457123 | 300.46 | 0.000000 |
| 635 | EI0644 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2008 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.67600 | 27.7180 | 0.2823523 | 7 | 9 | 26.48767 | 27.375 | 1.8419546 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7457123 | 300.46 | 0.000000 |
| 636 | EI0645 | CD092 | SI165 | 0.0000000 | % | NA | Table 2 | 2008 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.67600 | 27.7180 | 0.2823523 | 7 | 9 | 26.48767 | 27.375 | 1.8419546 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7457123 | 300.46 | 0.000000 |
| 637 | EI0646 | CD092 | SI165 | 0.1100000 | % | NA | Table 2 | 2008 | Jul-Sep | Jul-Sep | Table 2 | Bermuda | Materials and Methods Spatial patterns of coral cover and disease prevalence p81 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 32.305060 | -64.73344 | 32.305060 | -64.73344 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 27.67600 | 27.7180 | 0.2823523 | 7 | 9 | 26.48767 | 27.375 | 1.8419546 | sum | 7 | summer | NA | NA | NA | 7.80000 | 26 | Figure 1 | 160000 | 0 | Coral_N aggregated for whole study | Belt | 130 | 30.0000 | 2.00 | 60.0000 | Materials and Methods Spatial patterns of coral cover and disease prevalence p81-82 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7457123 | 300.46 | 0.000000 |
| 638 | EI0647 | CD093 | SI166 | 2.0000000 | % | NA | Table 2 | 1996 | 0 | 0 | Table 2 | Triangulos Este, Campeche Bank Gulf of Mexico | Materials and Methods Study sites p4 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.860450 | -92.53477 | 21.860450 | -92.53477 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.72500 | 28.7250 | NA | 7 | 7 | 28.71267 | 28.725 | 0.2237553 | sum | 7 | summer | NA | NA | NA | 0.07200 | 3 | Materials and Methods Method p5 | 86 | 0 | NA | Belt | 6 | 20.0000 | 0.60 | 12.0000 | Materials and Methods Methods p5 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4149933 | 302.25 | 2.615693 |
| 639 | EI0648 | CD093 | SI166 | 37.0000000 | % | NA | Table 2 | 2001 | 0 | 0 | Table 2 | Triangulos Este, Campeche Bank Gulf of Mexico | Materials and Methods Study sites p4 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.860450 | -92.53477 | 21.860450 | -92.53477 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.70500 | 28.7050 | NA | 7 | 7 | 28.73767 | 28.705 | 0.7815123 | sum | 7 | summer | NA | NA | NA | 0.15600 | 6 | Materials and Methods Method p5 | 533 | 0 | NA | Belt | 39 | 10.0000 | 0.40 | 4.0000 | Materials and Methods Methods p5 | NA | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5099945 | 302.25 | 1.014283 |
| 640 | EI0649 | CD093 | SI167 | 4.0000000 | % | NA | Table 2 | 1996 | 0 | 0 | Table 2 | Cayos Arcas, Campeche Bank Gulf of Mexico | Materials and Methods Study sites p4 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.159020 | -91.95568 | 21.159020 | -91.95568 | GoogleMaps Cayos Arcas | NA | NA | NA | Atlantic Ocean | 28.58800 | 28.5880 | NA | 7 | 7 | 28.57467 | 28.588 | 0.1953413 | sum | 7 | summer | NA | NA | NA | 0.07200 | 3 | Materials and Methods Method p5 | 153 | 0 | NA | Belt | 6 | 20.0000 | 0.60 | 12.0000 | Materials and Methods Methods p5 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2789230 | 302.00 | 3.661409 |
| 641 | EI0650 | CD093 | SI167 | 34.0000000 | % | NA | Table 2 | 2001 | 0 | 0 | Table 2 | Cayos Arcas, Campeche Bank Gulf of Mexico | Materials and Methods Study sites p4 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 21.159020 | -91.95568 | 21.159020 | -91.95568 | GoogleMaps Cayos Arcas | NA | NA | NA | Atlantic Ocean | 28.57000 | 28.5700 | NA | 7 | 7 | 28.60600 | 28.570 | 0.7266699 | sum | 7 | summer | NA | NA | NA | 0.15600 | 17 | Materials and Methods Method p5 | 253 | 0 | NA | Belt | 42 | 10.0000 | 0.40 | 4.0000 | Materials and Methods Methods p5 | NA | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3028564 | 302.00 | 0.000000 |
| 642 | EI0651 | CD093 | SI168 | 0.0000000 | % | NA | Table 2 | 1998 | 0 | 0 | Table 2 | Puerto Morelos, Yucatan Peninsula | Materials and Methods Study sites p4 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 20.849220 | -86.87585 | 20.849220 | -86.87585 | GoogleMaps Puerto Morelo | NA | NA | NA | Atlantic Ocean | 29.23500 | 29.2350 | NA | 7 | 7 | 29.32700 | 29.235 | 0.4176696 | sum | 7 | summer | NA | NA | NA | 0.30000 | 3 | Materials and Methods Method p5 | 212 | 0 | NA | Quadrat | 3 | 50.0000 | 2.00 | 100.0000 | Materials and Methods Methods p5 | NA | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3585587 | 301.85 | 0.000000 |
| 643 | EI0652 | CD093 | SI168 | 26.0000000 | % | NA | Table 2 | 2001 | 0 | 0 | Table 2 | Puerto Morelos, Yucatan Peninsula | Materials and Methods Study sites p4 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 20.849220 | -86.87585 | 20.849220 | -86.87585 | GoogleMaps Puerto Morelo | NA | NA | NA | Atlantic Ocean | 28.69000 | 28.6900 | NA | 7 | 7 | 28.69933 | 28.690 | 0.4890662 | sum | 7 | summer | NA | NA | NA | 0.94200 | 3 | Materials and Methods Method p5 | 68 | 0 | NA | Circle | 3 | 10.0000 | NA | 314.0000 | Materials and Methods Methods p5 | length is diameter | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6789703 | 301.85 | 0.000000 |
| 644 | EI0653 | CD094 | SI169 | 2.4000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Lalaan, San Jose, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 466 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 645 | EI0654 | CD094 | SI169 | 2.4000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Calo River, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 124 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 646 | EI0655 | CD094 | SI169 | 2.7000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Cangmating, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 333 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 647 | EI0656 | CD094 | SI169 | 1.2000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Maslog River, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 335 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 648 | EI0657 | CD094 | SI169 | 18.5000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Caloncalong Pt, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 363 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 649 | EI0658 | CD094 | SI169 | 14.3000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Agan-an North, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 582 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 650 | EI0659 | CD094 | SI169 | 5.3000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Agan-an South, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 397 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 651 | EI0660 | CD094 | SI169 | 4.7000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Airport Runway, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 322 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 652 | EI0661 | CD094 | SI169 | 29.4000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Piapi, Escano, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 248 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 653 | EI0662 | CD094 | SI169 | 43.6000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Looc, Dumaguete City Pier, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 351 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 654 | EI0663 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Mangnao, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 252 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 655 | EI0664 | CD094 | SI169 | 0.3000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Banilad, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 670 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 656 | EI0665 | CD094 | SI169 | 1.8000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Poblacion, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 954 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 657 | EI0666 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Masaplod, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 190 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 658 | EI0667 | CD094 | SI169 | 0.4000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Bonbonan, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 256 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 659 | EI0668 | CD094 | SI169 | 0.9000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Sillon Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 551 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 660 | EI0669 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Panagsama, Cebu | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 872 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 661 | EI0670 | CD094 | SI169 | 0.2000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Pescador Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 611 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 662 | EI0671 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Calagcalag, Negros | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 301 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 663 | EI0672 | CD094 | SI169 | 5.7000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Bato Cebu | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 351 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 664 | EI0673 | CD094 | SI169 | 53.7000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Looc, Cebu | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 67 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 665 | EI0674 | CD094 | SI169 | 11.5000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Sumilon Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 288 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 666 | EI0675 | CD094 | SI169 | 0.6000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Alona, Panglao Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 311 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 667 | EI0676 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Tubod, Siquijor Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 335 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 668 | EI0677 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Olango Island, Cebu Strait | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 243 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 669 | EI0678 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Snake Island, Honda Bay, Palawan | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 223 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 670 | EI0679 | CD094 | SI169 | 4.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Sabang Bay, Palawan | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 149 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 671 | EI0680 | CD094 | SI169 | 15.3000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Lalaan, San Jose, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 380 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 672 | EI0681 | CD094 | SI169 | 12.3000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Calo River, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 122 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 673 | EI0682 | CD094 | SI169 | 25.2000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Cangmating, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 230 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 674 | EI0683 | CD094 | SI169 | 23.1000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Maslog River, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 269 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 675 | EI0684 | CD094 | SI169 | 32.8000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Caloncalong Pt, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 314 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 676 | EI0685 | CD094 | SI169 | 39.1000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Agan-an North, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 432 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 677 | EI0686 | CD094 | SI169 | 38.5000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Agan-an South, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 392 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 678 | EI0687 | CD094 | SI169 | 19.5000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Airport Runway, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 298 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 679 | EI0688 | CD094 | SI169 | 2.2000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Piapi, Escano, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 229 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 680 | EI0689 | CD094 | SI169 | 6.2000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Looc, Dumaguete City Pier, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 291 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 681 | EI0690 | CD094 | SI169 | 0.4000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Mangnao, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 238 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 682 | EI0691 | CD094 | SI169 | 4.4000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Banilad, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 496 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 683 | EI0692 | CD094 | SI169 | 9.2000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Poblacion, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 328 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 684 | EI0693 | CD094 | SI169 | 0.9000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Masaplod, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 110 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 685 | EI0694 | CD094 | SI169 | 1.8000000 | % | NA | Table 1 | 2003 | Mar-Apr | Mar-Apr | Materials and Methods Gradient study p11 | Bonbonan, Negros Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 27.97500 | 27.9750 | 0.9333821 | 3 | 4 | 29.55200 | 29.570 | 0.3053984 | spr | 3 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 223 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 686 | EI0695 | CD094 | SI169 | 15.9000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Sillon Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 383 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 687 | EI0696 | CD094 | SI169 | 1.6000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Panagsama, Cebu | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 701 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 688 | EI0697 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Pescador Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 426 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 689 | EI0698 | CD094 | SI169 | 11.2000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Calagcalag, Negros | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 196 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 690 | EI0699 | CD094 | SI169 | 4.9000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Bato Cebu | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 325 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 691 | EI0700 | CD094 | SI169 | 3.9000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Looc, Cebu | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 52 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 692 | EI0701 | CD094 | SI169 | 0.7000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Sumilon Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 136 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 693 | EI0702 | CD094 | SI169 | 1.7000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Alona, Panglao Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 121 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 694 | EI0703 | CD094 | SI169 | 0.9000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Tubod, Siquijor Island | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 222 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 695 | EI0704 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Olango Island, Cebu Strait | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 225 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 696 | EI0705 | CD094 | SI169 | 5.8000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Snake Island, Honda Bay, Palawan | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 104 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 697 | EI0706 | CD094 | SI169 | 0.0000000 | % | NA | Table 1 | 2003 | Apr-May | Apr-May | Materials and Methods Region-wide study p11 | Sabang Bay, Palawan | Table 1 | Coral Triangle & SE Asia | Southeast Asia | 11.000000 | 122.37939 | 11.003200 | 123.50017 | GoogleMaps Visayas | NA | NA | NA | Pacific Ocean | 29.09750 | 29.0975 | 0.6540732 | 4 | 5 | 29.55200 | 29.570 | 0.3053984 | spr | 4 | spring | NA | NA | NA | 0.12000 | 1 | Table 1 | 149 | 1 | Mixed porites sp | Belt | 6 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Transect methodology p10 | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4542389 | 302.67 | 0.000000 |
| 698 | EI0707 | CD095 | SI170 | 3.7000000 | % | NA | Table 1 | 2001 | Jun-Aug | Jun-Aug | Methods and Materials Survey and analytical techniques p127 | Butler Bay | Table 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.255000 | -62.52000 | 18.255000 | -62.52000 | Methods and Materials Study sites p126 | NA | NA | NA | Atlantic Ocean | 28.25367 | 28.2030 | 0.3338951 | 6 | 8 | 28.25367 | 28.203 | 0.3338951 | sum | 6 | summer | NA | NA | NA | 0.30200 | 1 | Table 1 | 1344 | 1 | NA | Belt | 7 | 20.0000 | 2.00 | 40.0000 | Methods and Materials Survey and analytical methods p127 | Transect length varied per transect due to environmental challenges, 20m on average; Study area metric in Moderator Data accurate to real study area size | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8007202 | 301.38 | 0.000000 |
| 699 | EI0708 | CD095 | SI171 | 13.6000000 | % | NA | Table 1 | 2001 | Jun-Aug | Jun-Aug | Methods and Materials Survey and analytical techniques p127 | Frederiksted | Table 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.233330 | -65.45833 | 18.233330 | -65.45833 | Methods and Materials Study sites p126 | NA | NA | NA | Atlantic Ocean | 28.32800 | 28.2780 | 0.3477070 | 6 | 8 | 28.32800 | 28.278 | 0.3477070 | sum | 6 | summer | NA | NA | NA | 0.34300 | 1 | Table 1 | 566 | 1 | NA | Belt | 7 | 20.0000 | 2.00 | 40.0000 | Methods and Materials Survey and analytical methods p127 | Transect length varied per transect due to environmental challenges, 20m on average; Study area metric in Moderator Data accurate to real study area size | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7428436 | 301.68 | 0.000000 |
| 700 | EI0709 | CD096 | SI172 | 64.7000000 | % | NA | Results Prevalence and severity of Gas | 2010 | Sep-Nov | Sep-Nov | Materials and Methods Study site and sample collection | Hardy Reef, Great Barrier Reef Marine Park | Materials and Methods Study site and sample collection | Western Pacific | Australia | -19.766667 | 149.25000 | -19.766667 | 149.25000 | Materials and Methods Study site and sample collection, GoogleMaps | NA | NA | near unused tourist platform | Pacific Ocean | 25.62033 | 25.6880 | 1.0651137 | 9 | 11 | 28.14100 | 28.305 | 0.1443891 | spr | 3 | spring | NA | NA | NA | 0.03000 | 1 | Materials and Methods Study site and sample collection | 419 | 0 | NA | Belt | 1 | 15.0000 | 2.00 | 30.0000 | Materials and Methods Prevalence and severity of Gas | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7885742 | 301.30 | 0.000000 |
| 701 | EI0710 | CD096 | SI172 | 68.8000000 | % | NA | Results Prevalence and severity of Gas | 2011 | Jul | Jul | Materials and Methods Study site and sample collection | Hardy Reef, Great Barrier Reef Marine Park | Materials and Methods Study site and sample collection | Western Pacific | Australia | -19.766667 | 149.25000 | -19.766667 | 149.25000 | Materials and Methods Study site and sample collection, GoogleMaps | NA | NA | near unused tourist platform | Pacific Ocean | 22.40500 | 22.4050 | NA | 7 | 7 | 28.06433 | 27.915 | 0.4194361 | win | 1 | winter | NA | NA | NA | 0.03000 | 1 | Materials and Methods Study site and sample collection | 336 | 0 | NA | Belt | 1 | 15.0000 | 2.00 | 30.0000 | Materials and Methods Prevalence and severity of Gas | NA | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9978333 | 301.30 | 0.000000 |
| 702 | EI0711 | CD097 | SI173 | 2.3000000 | % | NA | Table 2 | 2004 | May-Jun | May-Jun | Results and Discussion p240 | Buck Island Reef National Monument | Materials and Methods p240 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.788090 | -64.62078 | 17.788090 | -64.62078 | GoogleMaps Buck Island Reef National Monument | NA | NA | Branching coral dominated | Atlantic Ocean | 27.48900 | 27.4890 | 0.5388148 | 5 | 6 | 28.27267 | 28.213 | 0.4355757 | spr | 5 | spring | NA | NA | NA | 114.00000 | 456 | Results and Discussion p240 | 1492 | 0 | Only included sites that had A palmata | Belt | 1 | 25.0000 | 10.00 | 250.0000 | Materials and Methods p240 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6646042 | 301.66 | 0.000000 |
| 703 | EI0712 | CD097 | SI173 | 3.4000000 | % | NA | Table 2 | 2004 | May-Jun | May-Jun | Results and Discussion p240 | Buck Island Reef National Monument | Materials and Methods p240 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.788090 | -64.62078 | 17.788090 | -64.62078 | GoogleMaps Buck Island Reef National Monument | NA | NA | Other hardbottom | Atlantic Ocean | 27.48900 | 27.4890 | 0.5388148 | 5 | 6 | 28.27267 | 28.213 | 0.4355757 | spr | 5 | spring | NA | NA | NA | 114.00000 | 456 | Results and Discussion p240 | 1000 | 0 | Only included sites that had A palmata | Belt | 1 | 25.0000 | 10.00 | 250.0000 | Materials and Methods p240 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6646042 | 301.66 | 0.000000 |
| 704 | EI0713 | CD099 | SI174 | 0.8000000 | % | NA | Figure 3 | 2011 | May | May | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 27.30300 | 27.3030 | NA | 5 | 5 | 29.76600 | 30.025 | 0.9386921 | spr | 5 | spring | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.9346466 | 302.77 | 3.815673 |
| 705 | EI0714 | CD099 | SI174 | 1.2000000 | % | NA | Figure 3 | 2011 | May | May | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 27.30300 | 27.3030 | NA | 5 | 5 | 29.76600 | 30.025 | 0.9386921 | spr | 5 | spring | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.9346466 | 302.77 | 3.815673 |
| 706 | EI0715 | CD099 | SI174 | 7.2000000 | % | NA | Figure 3 | 2011 | Jun | Jun | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 28.72500 | 28.7250 | NA | 6 | 6 | 29.76600 | 30.025 | 0.9386921 | sum | 6 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.7064133 | 302.77 | 3.815673 |
| 707 | EI0716 | CD099 | SI174 | 5.6000000 | % | NA | Figure 3 | 2011 | Jul | Jul | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.02500 | 30.0250 | NA | 7 | 7 | 29.76600 | 30.025 | 0.9386921 | sum | 7 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.4257050 | 302.77 | 2.498545 |
| 708 | EI0717 | CD099 | SI174 | 2.8000000 | % | NA | Figure 3 | 2011 | Jul | Jul | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.02500 | 30.0250 | NA | 7 | 7 | 29.76600 | 30.025 | 0.9386921 | sum | 7 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.4257050 | 302.77 | 2.498545 |
| 709 | EI0718 | CD099 | SI174 | 1.2000000 | % | NA | Figure 3 | 2011 | Jul | Jul | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.02500 | 30.0250 | NA | 7 | 7 | 29.76600 | 30.025 | 0.9386921 | sum | 7 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.4257050 | 302.77 | 2.498545 |
| 710 | EI0719 | CD099 | SI174 | 4.0000000 | % | NA | Figure 3 | 2011 | Sep | Sep | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.01300 | 30.0130 | NA | 9 | 9 | 29.76600 | 30.025 | 0.9386921 | aut | 9 | fall | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.4646606 | 302.77 | 4.991414 |
| 711 | EI0720 | CD099 | SI174 | 2.8000000 | % | NA | Figure 3 | 2011 | Sep | Sep | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.01300 | 30.0130 | NA | 9 | 9 | 29.76600 | 30.025 | 0.9386921 | aut | 9 | fall | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.4646606 | 302.77 | 4.991414 |
| 712 | EI0721 | CD099 | SI174 | 3.2000000 | % | NA | Figure 3 | 2011 | Nov | Nov | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 26.72800 | 26.7280 | NA | 11 | 11 | 29.76600 | 30.025 | 0.9386921 | aut | 11 | fall | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.7092896 | 302.77 | 6.132822 |
| 713 | EI0722 | CD099 | SI174 | 7.6000000 | % | NA | Figure 3 | 2012 | May | May | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 26.95800 | 26.9580 | NA | 5 | 5 | 29.36267 | 29.610 | 0.8581618 | spr | 5 | spring | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.3092804 | 302.77 | 6.132822 |
| 714 | EI0723 | CD099 | SI174 | 19.2000000 | % | NA | Figure 3 | 2012 | Jun | Jun | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 28.40800 | 28.4080 | NA | 6 | 6 | 29.36267 | 29.610 | 0.8581618 | sum | 6 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.1399689 | 302.77 | 6.132822 |
| 715 | EI0724 | CD099 | SI174 | 17.2000000 | % | NA | Figure 3 | 2012 | Jul | Jul | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 29.61000 | 29.6100 | NA | 7 | 7 | 29.36267 | 29.610 | 0.8581618 | sum | 7 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 1.1399689 | 302.77 | 6.132822 |
| 716 | EI0725 | CD099 | SI174 | 13.6000000 | % | NA | Figure 3 | 2012 | Aug | Aug | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.07000 | 30.0700 | NA | 8 | 8 | 29.36267 | 29.610 | 0.8581618 | sum | 8 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.8317795 | 302.77 | 3.472839 |
| 717 | EI0726 | CD099 | SI174 | 14.8000000 | % | NA | Figure 3 | 2012 | Aug | Aug | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 30.07000 | 30.0700 | NA | 8 | 8 | 29.36267 | 29.610 | 0.8581618 | sum | 8 | summer | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.8317795 | 302.77 | 3.472839 |
| 718 | EI0727 | CD099 | SI174 | 36.0000000 | % | NA | Figure 3 | 2012 | Sep | Sep | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 29.71800 | 29.7180 | NA | 9 | 9 | 29.36267 | 29.610 | 0.8581618 | aut | 9 | fall | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.5442810 | 302.77 | 1.141408 |
| 719 | EI0728 | CD099 | SI174 | 28.4000000 | % | NA | Figure 3 | 2012 | Nov | Nov | Figure 3 | Upper Florida Keys National Marine Sanctuary | Materials and Methods Study sites | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.973611 | -80.45856 | 24.973611 | -80.45856 | Table 1, averaged across three wild sites | NA | NA | Prevalence extacted using MetaDigitise in Rstudio, n = 3; wild sites | Atlantic Ocean | 26.22000 | 26.2200 | NA | 11 | 11 | 29.36267 | 29.610 | 0.8581618 | aut | 11 | fall | NA | NA | NA | 0.70791 | 3 | Table 1 | NA | 0 | NA | Circle | 1 | 8.6667 | NA | 235.9700 | Materials and Methods Surveillance | radius averaged from 3 sizes | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Previously characterised as “WBD” but paper claims this is innacurate and more generall describe it as TL | 0.5964203 | 302.77 | 0.000000 |
| 720 | EI0729 | CD098 | SI175 | 2.9000000 | % | 1.5 | Results and Discussion p98 | 2002 | 0 | 0 | Materials and Methods p98 | Navassa | Materials and Methods p97 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.409420 | -75.02177 | 18.409420 | -75.02177 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.94300 | 28.9430 | NA | 7 | 7 | 28.96033 | 28.943 | 0.5362104 | sum | 7 | summer | NA | NA | NA | 0.01400 | 1 | Figure 1 | NA | 1 | NA | Quadrat | 14 | 1.0000 | 1.00 | 1.0000 | Materials and Methods p98 | NA | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7442932 | 302.11 | 1.115709 |
| 721 | EI0730 | CD098 | SI175 | 16.8000000 | % | 4.3 | Results and Discussion p98 | 2004 | 0 | 0 | Materials and Methods p98 | Navassa | Materials and Methods p97 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.409420 | -75.02177 | 18.409420 | -75.02177 | Figure 1, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.05300 | 29.0530 | NA | 7 | 7 | 29.00300 | 29.053 | 0.3725250 | sum | 7 | summer | NA | NA | NA | 0.01400 | 1 | Figure 1 | NA | 1 | NA | Quadrat | 14 | 1.0000 | 1.00 | 1.0000 | Materials and Methods p98 | NA | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2857056 | 302.11 | 2.314272 |
| 722 | EI0731 | CD100 | SI176 | 0.3400000 | % | 0.13, 0.74 | Table 2 | 2010 | Oct-Nov | Oct-Nov | Materials and Methods p160 | Magoodhoo Island, Faafu Atoll, Republic of Maldives | Materials and Methods p160 | Western Indian Ocean | Central Indian | 3.066667 | 72.95000 | 3.066667 | 72.95000 | Materials and Methods p160, GoogleMaps | NA | NA | error in LL and UL 95% bootstrap CI | Indian Ocean | 28.57650 | 28.5765 | 0.0544470 | 10 | 11 | 29.37700 | 29.365 | 0.3551516 | aut | 10 | fall | NA | NA | NA | 0.60000 | 8 | Materials and Methods p160 | 2761 | 1 | Coral_N aggregated from whole study | Belt | 24 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p160 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5685730 | 302.67 | 0.000000 |
| 723 | EI0732 | CD100 | SI176 | 0.7000000 | % | 0.41, 0.99 | Table 2 | 2010 | Oct-Nov | Oct-Nov | Materials and Methods p160 | Magoodhoo Island, Faafu Atoll, Republic of Maldives | Materials and Methods p160 | Western Indian Ocean | Central Indian | 3.066667 | 72.95000 | 3.066667 | 72.95000 | Materials and Methods p160, GoogleMaps | NA | NA | error in LL and UL 95% bootstrap CI | Indian Ocean | 28.57650 | 28.5765 | 0.0544470 | 10 | 11 | 29.37700 | 29.365 | 0.3551516 | aut | 10 | fall | NA | NA | NA | 0.60000 | 8 | Materials and Methods p160 | 2761 | 1 | Coral_N aggregated from whole study | Belt | 24 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p160 | NA | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5685730 | 302.67 | 0.000000 |
| 724 | EI0733 | CD100 | SI176 | 0.1800000 | % | 0.07, 0.31 | Table 2 | 2010 | Oct-Nov | Oct-Nov | Materials and Methods p160 | Magoodhoo Island, Faafu Atoll, Republic of Maldives | Materials and Methods p160 | Western Indian Ocean | Central Indian | 3.066667 | 72.95000 | 3.066667 | 72.95000 | Materials and Methods p160, GoogleMaps | NA | NA | error in LL and UL 95% bootstrap CI | Indian Ocean | 28.57650 | 28.5765 | 0.0544470 | 10 | 11 | 29.37700 | 29.365 | 0.3551516 | aut | 10 | fall | NA | NA | NA | 0.60000 | 8 | Materials and Methods p160 | 2761 | 1 | Coral_N aggregated from whole study | Belt | 24 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p160 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5685730 | 302.67 | 0.000000 |
| 725 | EI0734 | CD100 | SI176 | 0.6400000 | % | 0.41, 0.92 | Table 2 | 2010 | Oct-Nov | Oct-Nov | Materials and Methods p160 | Magoodhoo Island, Faafu Atoll, Republic of Maldives | Materials and Methods p160 | Western Indian Ocean | Central Indian | 3.066667 | 72.95000 | 3.066667 | 72.95000 | Materials and Methods p160, GoogleMaps | NA | NA | error in LL and UL 95% bootstrap CI | Indian Ocean | 28.57650 | 28.5765 | 0.0544470 | 10 | 11 | 29.37700 | 29.365 | 0.3551516 | aut | 10 | fall | NA | NA | NA | 0.60000 | 8 | Materials and Methods p160 | 2761 | 1 | Coral_N aggregated from whole study | Belt | 24 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p160 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5685730 | 302.67 | 0.000000 |
| 726 | EI0735 | CD101 | SI177 | 40.4900000 | % | 2.12 | Results and Discussion White syndrome prevalence p5 | 2015 | May | May | Material and Methods Study site p2 | Water Discharge Barat, Paiton Power Plant, Probolinggo | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 7.714317 | 113.59846 | 7.714317 | 113.59846 | Table 1, GoogleMaps | NA | NA | Assumed error is SE | Pacific Ocean | 30.57000 | 30.5700 | NA | 5 | 5 | 30.18867 | 29.783 | 0.3977517 | spr | 5 | spring | NA | NA | NA | 0.08000 | 1 | Figure 1 | NA | 1 | NA | Belt | 4 | 20.0000 | 1.00 | 20.0000 | Material and Methods Observation Method p2 | NA | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3082047 | 302.66 | 2.211404 |
| 727 | EI0736 | CD101 | SI178 | 13.5300000 | % | 11.5 | Results and Discussion White syndrome prevalence p5 | 2015 | May | May | Material and Methods Study site p2 | Water Discharge Timur, Paiton Power Plant, Probolinggo | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 7.715828 | 113.59833 | 7.715828 | 113.59833 | Table 1, GoogleMaps | NA | NA | Assumed error is SE | Pacific Ocean | 30.57000 | 30.5700 | NA | 5 | 5 | 30.18867 | 29.783 | 0.3977517 | spr | 5 | spring | NA | NA | NA | 0.08000 | 1 | Figure 1 | NA | 1 | NA | Belt | 4 | 20.0000 | 1.00 | 20.0000 | Material and Methods Observation Method p2 | NA | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3082047 | 302.66 | 2.211404 |
| 728 | EI0737 | CD101 | SI179 | 6.4400000 | % | 3.6 | Results and Discussion White syndrome prevalence p5 | 2015 | May | May | Material and Methods Study site p2 | Water Intake, Paiton Power Plant, Probolinggo | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | 7.711750 | 113.58756 | 7.711750 | 113.58756 | Table 1, GoogleMaps | NA | NA | Assumed error is SE | Pacific Ocean | 30.57000 | 30.5700 | NA | 5 | 5 | 30.18867 | 29.783 | 0.3977517 | spr | 5 | spring | NA | NA | NA | 0.08000 | 1 | Figure 1 | NA | 1 | NA | Belt | 4 | 20.0000 | 1.00 | 20.0000 | Material and Methods Observation Method p2 | NA | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3082047 | 302.66 | 2.211404 |
| 729 | EI0804 | CD103 | SI180 | 2.3000000 | % | NA | Results p261 | 2005 | Dec-Feb | Dec-Feb | Results p261 | Great Barrier Reef | Figure 2 | Western Pacific | Australia | -16.824100 | 146.01516 | -16.824100 | 146.01516 | GoogleMaps Cairns coast, Figure 2 approximate middle point | NA | NA | NA | Pacific Ocean | 28.87700 | 28.9480 | 0.1119065 | 12 | 2 | 28.87700 | 28.948 | 0.1119065 | aut | 6 | summer | NA | NA | NA | 4.32000 | 18 | Results p261 | 96148 | 1 | NA | Belt | 108 | 20.0000 | 2.00 | 40.0000 | Materials and Methods p259 | NA | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4110870 | 301.89 | 0.000000 |
| 730 | EI0805 | CD103 | SI180 | 1.2000000 | % | NA | Results p261 | 2006 | Dec-Feb | Dec-Feb | Results p261 | Great Barrier Reef | Figure 2 | Western Pacific | Australia | -16.824100 | 146.01516 | -16.824100 | 146.01516 | GoogleMaps Cairns coast, Figure 2 approximate middle point | NA | NA | NA | Pacific Ocean | 27.99300 | 28.3880 | 0.8084396 | 12 | 2 | 27.99300 | 28.388 | 0.8084396 | aut | 6 | summer | NA | NA | NA | 4.32000 | 18 | Results p261 | 91552 | 1 | NA | Belt | 108 | 20.0000 | 2.00 | 40.0000 | Materials and Methods p259 | NA | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4164429 | 301.89 | 2.390015 |
| 731 | EI0807 | CD105 | SI181 | 0.0672646 | % | 0.31390135 | Figure 2 | 2006 | Sep | Sep | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 23.77500 | 23.7750 | NA | 9 | 9 | 27.86967 | 28.253 | 0.7165430 | spr | 3 | spring | 0.5436931 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6607056 | 301.89 | 0.000000 |
| 732 | EI0808 | CD105 | SI181 | 0.5156951 | % | 0.44843049 | Figure 2 | 2006 | Oct | Oct | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 24.80800 | 24.8080 | NA | 10 | 10 | 27.86967 | 28.253 | 0.7165430 | spr | 4 | spring | 0.7767044 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6607056 | 301.89 | 0.000000 |
| 733 | EI0809 | CD105 | SI181 | 3.1838565 | % | 2.17488789 | Figure 2 | 2006 | Dec | Dec | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 27.04300 | 27.0430 | NA | 12 | 12 | 27.86967 | 28.253 | 0.7165430 | sum | 6 | summer | 3.7670163 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3724976 | 301.89 | 0.000000 |
| 734 | EI0810 | CD105 | SI181 | 9.6636771 | % | 5.04484305 | Figure 2 | 2007 | Feb | Feb | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.31300 | 28.3130 | NA | 2 | 2 | 28.65267 | 28.798 | 0.2448296 | sum | 8 | summer | 8.7379245 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4025040 | 301.89 | 0.000000 |
| 735 | EI0811 | CD105 | SI181 | 0.5381166 | % | 0.51569507 | Figure 2 | 2007 | Apr | Apr | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 26.56300 | 26.5630 | NA | 4 | 4 | 28.65267 | 28.798 | 0.2448296 | aut | 10 | fall | 0.8932101 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2185669 | 301.89 | 0.000000 |
| 736 | EI0812 | CD105 | SI181 | 0.6950673 | % | 0.40358744 | Figure 2 | 2007 | May | May | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 25.29500 | 25.2950 | NA | 5 | 5 | 28.65267 | 28.798 | 0.2448296 | aut | 11 | fall | 0.9885833 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2185669 | 301.89 | 0.000000 |
| 737 | EI0813 | CD105 | SI181 | 0.4484305 | % | 0.22421525 | Figure 2 | 2007 | Jul | Jul | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 22.73800 | 22.7380 | NA | 7 | 7 | 28.65267 | 28.798 | 0.2448296 | win | 1 | winter | 0.5492129 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5685730 | 301.89 | 0.000000 |
| 738 | EI0814 | CD105 | SI181 | 0.4708520 | % | 0.22421525 | Figure 2 | 2007 | Sep | Sep | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 23.82500 | 23.8250 | NA | 9 | 9 | 28.65267 | 28.798 | 0.2448296 | spr | 3 | spring | 0.5492129 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0971375 | 301.89 | 0.000000 |
| 739 | EI0815 | CD105 | SI181 | 1.8385650 | % | 0.78475336 | Figure 2 | 2007 | Nov | Nov | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 27.05800 | 27.0580 | NA | 11 | 11 | 28.65267 | 28.798 | 0.2448296 | spr | 5 | spring | 1.9222453 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4514160 | 301.89 | 0.000000 |
| 740 | EI0816 | CD105 | SI181 | 3.2286996 | % | 0.85201794 | Figure 2 | 2008 | Jan | Jan | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.79800 | 28.7980 | NA | 1 | 1 | 28.48367 | 28.553 | 0.1157854 | sum | 7 | summer | 2.0870092 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1142578 | 301.89 | 0.000000 |
| 741 | EI0817 | CD105 | SI181 | 3.0269058 | % | 0.87443946 | Figure 2 | 2008 | Feb | Feb | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.79000 | 28.7900 | NA | 2 | 2 | 28.48367 | 28.553 | 0.1157854 | sum | 8 | summer | 2.1419305 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4410629 | 301.89 | 0.000000 |
| 742 | EI0818 | CD105 | SI181 | 0.1793722 | % | 6.73E-02 | Figure 2 | 2008 | Mar | Mar | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 27.65000 | 27.6500 | NA | 3 | 3 | 28.48367 | 28.553 | 0.1157854 | aut | 9 | fall | 0.1647639 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4410629 | 301.89 | 0.000000 |
| 743 | EI0819 | CD105 | SI181 | 0.3587444 | % | 0.2690583 | Figure 2 | 2008 | Apr | Apr | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 26.38800 | 26.3880 | NA | 4 | 4 | 28.48367 | 28.553 | 0.1157854 | aut | 10 | fall | 0.4660226 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4410629 | 301.89 | 0.000000 |
| 744 | EI0820 | CD105 | SI181 | 0.1345291 | % | 0.15695067 | Figure 2 | 2008 | Aug | Aug | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 22.66000 | 22.6600 | NA | 8 | 8 | 28.48367 | 28.553 | 0.1157854 | win | 2 | winter | 0.3844491 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9142761 | 301.89 | 0.000000 |
| 745 | EI0821 | CD105 | SI181 | 0.7174888 | % | 0.20179372 | Figure 2 | 2008 | Nov | Nov | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 27.29300 | 27.2930 | NA | 11 | 11 | 28.48367 | 28.553 | 0.1157854 | spr | 5 | spring | 0.4942917 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6057129 | 301.89 | 0.000000 |
| 746 | EI0822 | CD105 | SI181 | 1.9955157 | % | 0.42600897 | Figure 2 | 2008 | Dec | Dec | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.54800 | 28.5480 | NA | 12 | 12 | 28.48367 | 28.553 | 0.1157854 | sum | 6 | summer | 1.0435046 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6057129 | 301.89 | 0.000000 |
| 747 | EI0823 | CD105 | SI181 | 3.2062780 | % | 0.82959641 | Figure 2 | 2009 | Jan | Jan | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.55300 | 28.5530 | NA | 1 | 1 | 28.42467 | 28.313 | 0.4285533 | sum | 7 | summer | 2.0320879 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4207001 | 301.89 | 0.000000 |
| 748 | EI0824 | CD105 | SI181 | 0.4035874 | % | 0.35874439 | Figure 2 | 2006 | Sep | Sep | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 23.77500 | 23.7750 | NA | 9 | 9 | 27.86967 | 28.253 | 0.7165430 | spr | 3 | spring | 0.6213635 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6607056 | 301.89 | 0.000000 |
| 749 | EI0825 | CD105 | SI181 | 4.2376682 | % | 0.98654709 | Figure 2 | 2006 | Oct | Oct | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 24.80800 | 24.8080 | NA | 10 | 10 | 27.86967 | 28.253 | 0.7165430 | spr | 4 | spring | 1.7087497 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6607056 | 301.89 | 0.000000 |
| 750 | EI0826 | CD105 | SI181 | 9.5515695 | % | 3.29596413 | Figure 2 | 2006 | Dec | Dec | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 27.04300 | 27.0430 | NA | 12 | 12 | 27.86967 | 28.253 | 0.7165430 | sum | 6 | summer | 5.7087773 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3724976 | 301.89 | 0.000000 |
| 751 | EI0827 | CD105 | SI181 | 9.5291480 | % | 4.61883408 | Figure 2 | 2007 | Feb | Feb | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.31300 | 28.3130 | NA | 2 | 2 | 28.65267 | 28.798 | 0.2448296 | sum | 8 | summer | 8.0000553 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4025040 | 301.89 | 0.000000 |
| 752 | EI0828 | CD105 | SI181 | 0.8744395 | % | 0.29147982 | Figure 2 | 2007 | Apr | Apr | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 26.56300 | 26.5630 | NA | 4 | 4 | 28.65267 | 28.798 | 0.2448296 | aut | 10 | fall | 0.5048579 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2185669 | 301.89 | 0.000000 |
| 753 | EI0829 | CD105 | SI181 | 0.9192825 | % | 0.38116592 | Figure 2 | 2007 | May | May | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 25.29500 | 25.2950 | NA | 5 | 5 | 28.65267 | 28.798 | 0.2448296 | aut | 11 | fall | 0.9336620 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.2185669 | 301.89 | 0.000000 |
| 754 | EI0830 | CD105 | SI181 | 0.9192825 | % | 0.38116592 | Figure 2 | 2007 | Jul | Jul | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 22.73800 | 22.7380 | NA | 7 | 7 | 28.65267 | 28.798 | 0.2448296 | win | 1 | winter | 0.9336620 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5685730 | 301.89 | 0.000000 |
| 755 | EI0831 | CD105 | SI181 | 2.7578475 | % | 0.85201794 | Figure 2 | 2007 | Sep | Sep | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 23.82500 | 23.8250 | NA | 9 | 9 | 28.65267 | 28.798 | 0.2448296 | spr | 3 | spring | 2.0870092 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0971375 | 301.89 | 0.000000 |
| 756 | EI0832 | CD105 | SI181 | 3.2062780 | % | 0.65022422 | Figure 2 | 2007 | Nov | Nov | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 27.05800 | 27.0580 | NA | 11 | 11 | 28.65267 | 28.798 | 0.2448296 | spr | 5 | spring | 1.5927175 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4514160 | 301.89 | 0.000000 |
| 757 | EI0833 | CD105 | SI181 | 1.1883408 | % | 0.82959641 | Figure 2 | 2008 | Jan | Jan | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.79800 | 28.7980 | NA | 1 | 1 | 28.48367 | 28.553 | 0.1157854 | sum | 7 | summer | 2.0320879 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1142578 | 301.89 | 0.000000 |
| 758 | EI0834 | CD105 | SI181 | 0.8520179 | % | 0.56053812 | Figure 2 | 2008 | Feb | Feb | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.79000 | 28.7900 | NA | 2 | 2 | 28.48367 | 28.553 | 0.1157854 | sum | 8 | summer | 1.3730324 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4410629 | 301.89 | 0.000000 |
| 759 | EI0835 | CD105 | SI181 | 0.2017937 | % | 4.48E-02 | Figure 2 | 2008 | Mar | Mar | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 27.65000 | 27.6500 | NA | 3 | 3 | 28.48367 | 28.553 | 0.1157854 | aut | 9 | fall | 0.1098426 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4410629 | 301.89 | 0.000000 |
| 760 | EI0836 | CD105 | SI181 | 0.6502242 | % | 0.38116592 | Figure 2 | 2008 | Apr | Apr | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 26.38800 | 26.3880 | NA | 4 | 4 | 28.48367 | 28.553 | 0.1157854 | aut | 10 | fall | 0.6601987 | NA | NA | 0.30000 | 1 | Figure 2 | NA | 1 | NA | Quadrat | 3 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4410629 | 301.89 | 0.000000 |
| 761 | EI0837 | CD105 | SI181 | 0.4708520 | % | 0.24663677 | Figure 2 | 2008 | Aug | Aug | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 22.66000 | 22.6600 | NA | 8 | 8 | 28.48367 | 28.553 | 0.1157854 | win | 2 | winter | 0.6041342 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9142761 | 301.89 | 0.000000 |
| 762 | EI0838 | CD105 | SI181 | 2.0852018 | % | 0.71748879 | Figure 2 | 2008 | Nov | Nov | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 27.29300 | 27.2930 | NA | 11 | 11 | 28.48367 | 28.553 | 0.1157854 | spr | 5 | spring | 1.7574814 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6057129 | 301.89 | 0.000000 |
| 763 | EI0839 | CD105 | SI181 | 1.6816143 | % | 0.47085202 | Figure 2 | 2008 | Dec | Dec | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.54800 | 28.5480 | NA | 12 | 12 | 28.48367 | 28.553 | 0.1157854 | sum | 6 | summer | 1.1533472 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6057129 | 301.89 | 0.000000 |
| 764 | EI0840 | CD105 | SI181 | 1.5919283 | % | 0.53811659 | Figure 2 | 2009 | Jan | Jan | Figure 2 | Pelorus Island, GBR Marine Park | Materials and Methods Study site and field surveys | Western Pacific | Australia | -18.550000 | 146.50000 | -18.550000 | 146.50000 | Materials and Methods Study site and field surveys, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Pacific Ocean | 28.55300 | 28.5530 | NA | 1 | 1 | 28.42467 | 28.313 | 0.4285533 | sum | 7 | summer | 1.3181111 | NA | NA | 0.60000 | 2 | Figure 2 | NA | 1 | NA | Quadrat | 6 | 10.0000 | 10.00 | 100.0000 | Materials and Methods Study site and field surveys | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4207001 | 301.89 | 0.000000 |
| 765 | EI0841 | CD106 | SI182 | 1.3000000 | % | 0.2090909 | Figure 3 | 2011 | Jan-Apr | Jan-Apr | Materials and Methods Study sites | Grand Recif of Tulear, SW Madagascar | Materials and Methods Study sites | Western Indian Ocean | West Indian | -23.089610 | 43.60424 | -23.089610 | 43.60424 | GoogleMaps Grand Recif, Madagascar | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 30 | Indian Ocean | 28.75625 | 28.8000 | 0.4377280 | 1 | 4 | 28.15600 | 28.135 | 0.3789367 | aut | 7 | summer | 1.1452381 | NA | NA | 3.00000 | 10 | Materials and Methods 2.1 White syndrome prevalence | NA | 1 | NA | Belt | 30 | 50.0000 | 2.00 | 100.0000 | Materials and Methods White syndrome prevalence | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3635712 | 302.33 | 3.911400 |
| 766 | EI0842 | CD106 | SI183 | 0.3818182 | % | 0.1636364 | Figure 3 | 2011 | Jan-Apr | Jan-Apr | Materials and Methods Study sites | Adavadoaka Reef System, Madagascar | Materials and Methods Study sites | Western Indian Ocean | West Indian | -22.076950 | 43.23053 | -22.076950 | 43.23053 | Figure 1, GoogleMaps | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 30 | Indian Ocean | 29.15725 | 29.1415 | 0.3968820 | 1 | 4 | 28.52700 | 28.543 | 0.3642640 | aut | 7 | summer | 0.8962733 | NA | NA | 3.00000 | 10 | Materials and Methods 2.1 White syndrome prevalence | NA | 1 | NA | Belt | 30 | 50.0000 | 2.00 | 100.0000 | Materials and Methods White syndrome prevalence | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.9271469 | 302.59 | 1.037137 |
| 767 | EI0843 | CD107 | SI184 | 4.3000000 | % | 1.8 | Results Differential disease susceptibility among color morphs of M capitata | 2007 | May | May | Materials and Methods Susceptibility to coral disease | Kaneohe Bay, Oahu, HI | Materials and Methods Study site | Western Pacific | Polynesia | 21.463460 | -157.81028 | 21.463460 | -157.81028 | GoogleMaps Kaneohe Bay | NA | NA | orange morph | Pacific Ocean | 25.00000 | 25.0000 | NA | 5 | 5 | 25.96267 | 25.940 | 0.3295856 | spr | 5 | spring | NA | NA | NA | 2.70000 | 9 | Materials and Methods Susceptibility to coral disease | 3078 | 0 | Coral_N includes both morphs | Belt | 18 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Susceptibility to coral disease | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6685486 | 300.02 | 0.000000 |
| 768 | EI0844 | CD107 | SI184 | 0.6000000 | % | 0.4 | Results Differential disease susceptibility among color morphs of M capitata | 2007 | May | May | Materials and Methods Susceptibility to coral disease | Kaneohe Bay, Oahu, HI | Materials and Methods Study site | Western Pacific | Polynesia | 21.463460 | -157.81028 | 21.463460 | -157.81028 | GoogleMaps Kaneohe Bay | NA | NA | red morph | Pacific Ocean | 25.00000 | 25.0000 | NA | 5 | 5 | 25.96267 | 25.940 | 0.3295856 | spr | 5 | spring | NA | NA | NA | 2.70000 | 9 | Materials and Methods Susceptibility to coral disease | 3078 | 0 | Coral_N includes both morphs | Belt | 18 | 25.0000 | 6.00 | 150.0000 | Materials and Methods Susceptibility to coral disease | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6685486 | 300.02 | 0.000000 |
| 769 | EI0845 | CD107 | SI184 | 15.7000000 | % | 3.6 | Results Differential disease susceptibility among color morphs of M capitata | 2011 | Jul | Jul | Materials and Methods Susceptibility to coral disease | Kaneohe Bay, Oahu, HI | Materials and Methods Study site | Western Pacific | Polynesia | 21.463460 | -157.81028 | 21.463460 | -157.81028 | GoogleMaps Kaneohe Bay | NA | NA | orange morph | Pacific Ocean | 25.47000 | 25.4700 | NA | 7 | 7 | 25.54367 | 25.470 | 0.2993762 | sum | 7 | summer | NA | NA | NA | 0.50000 | 10 | Materials and Methods Susceptibility to coral disease | 1370 | 0 | Coral_N includes both morphs | Belt | 10 | 50.0000 | 1.00 | 50.0000 | Materials and Methods Susceptibility to coral disease | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1885529 | 300.02 | 0.000000 |
| 770 | EI0846 | CD107 | SI184 | 3.4000000 | % | 0.7 | Results Differential disease susceptibility among color morphs of M capitata | 2011 | Jul | Jul | Materials and Methods Susceptibility to coral disease | Kaneohe Bay, Oahu, HI | Materials and Methods Study site | Western Pacific | Polynesia | 21.463460 | -157.81028 | 21.463460 | -157.81028 | GoogleMaps Kaneohe Bay | NA | NA | red morph | Pacific Ocean | 25.47000 | 25.4700 | NA | 7 | 7 | 25.54367 | 25.470 | 0.2993762 | sum | 7 | summer | NA | NA | NA | 0.50000 | 10 | Materials and Methods Susceptibility to coral disease | 1370 | 0 | Coral_N includes both morphs | Belt | 10 | 50.0000 | 1.00 | 50.0000 | Materials and Methods Susceptibility to coral disease | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1885529 | 300.02 | 0.000000 |
| 771 | EI0847 | CD108 | SI185 | 3.6000000 | % | NA | Table 1 | 2008 | 0 | 0 | Table 1 | Similan Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 10.961810 | 97.69758 | 10.961810 | 97.69758 | GoogleMaps Similan Island | NA | NA | NA | Indian Ocean | 28.61000 | 28.6100 | NA | 7 | 7 | 28.61033 | 28.610 | 0.3774997 | sum | 7 | summer | NA | NA | NA | 1.20000 | 10 | Table 1 | 1030 | 0 | Coral_N aggregated over entire sampling year | Belt | 30 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2599792 | 302.78 | 0.000000 |
| 772 | EI0848 | CD108 | SI185 | 2.1000000 | % | NA | Table 1 | 2008 | 0 | 0 | Table 1 | Similan Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 10.961810 | 97.69758 | 10.961810 | 97.69758 | GoogleMaps Similan Island | NA | NA | NA | Indian Ocean | 28.61000 | 28.6100 | NA | 7 | 7 | 28.61033 | 28.610 | 0.3774997 | sum | 7 | summer | NA | NA | NA | 1.20000 | 10 | Table 1 | 1030 | 0 | Coral_N aggregated over entire sampling year | Belt | 30 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2599792 | 302.78 | 0.000000 |
| 773 | EI0849 | CD108 | SI185 | 16.4000000 | % | NA | Table 1 | 2008 | 0 | 0 | Table 1 | Similan Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 10.961810 | 97.69758 | 10.961810 | 97.69758 | GoogleMaps Similan Island | NA | NA | NA | Indian Ocean | 28.61000 | 28.6100 | NA | 7 | 7 | 28.61033 | 28.610 | 0.3774997 | sum | 7 | summer | NA | NA | NA | 1.20000 | 10 | Table 1 | 1030 | 0 | Coral_N aggregated over entire sampling year | Belt | 30 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2599792 | 302.78 | 0.000000 |
| 774 | EI0850 | CD108 | SI185 | 4.8000000 | % | NA | Table 1 | 2010 | Nov | Nov | Table 1 | Similan Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 10.961810 | 97.69758 | 10.961810 | 97.69758 | GoogleMaps Similan Island | NA | NA | NA | Indian Ocean | 28.55300 | 28.5530 | NA | 11 | 11 | 29.22767 | 29.285 | 0.4318647 | aut | 11 | fall | NA | NA | NA | 0.60000 | 5 | Table 1 | 312 | 0 | Coral_N aggregated over entire sampling year | Belt | 15 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5142822 | 302.78 | 11.725703 |
| 775 | EI0851 | CD108 | SI185 | 0.6000000 | % | NA | Table 1 | 2010 | Nov | Nov | Table 1 | Similan Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 10.961810 | 97.69758 | 10.961810 | 97.69758 | GoogleMaps Similan Island | NA | NA | NA | Indian Ocean | 28.55300 | 28.5530 | NA | 11 | 11 | 29.22767 | 29.285 | 0.4318647 | aut | 11 | fall | NA | NA | NA | 0.60000 | 5 | Table 1 | 312 | 0 | Coral_N aggregated over entire sampling year | Belt | 15 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5142822 | 302.78 | 11.725703 |
| 776 | EI0852 | CD108 | SI185 | 8.0000000 | % | NA | Table 1 | 2010 | Nov | Nov | Table 1 | Similan Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 10.961810 | 97.69758 | 10.961810 | 97.69758 | GoogleMaps Similan Island | NA | NA | NA | Indian Ocean | 28.55300 | 28.5530 | NA | 11 | 11 | 29.22767 | 29.285 | 0.4318647 | aut | 11 | fall | NA | NA | NA | 0.60000 | 5 | Table 1 | 312 | 0 | Coral_N aggregated over entire sampling year | Belt | 15 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5142822 | 302.78 | 11.725703 |
| 777 | EI0853 | CD108 | SI186 | 0.8000000 | % | NA | Table 1 | 2009 | 0 | 0 | Table 1 | Surin Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 9.454450 | 97.87704 | 9.454450 | 97.87704 | GoogleMaps Surin Islands | NA | NA | NA | Indian Ocean | 29.04500 | 29.0450 | NA | 7 | 7 | 28.96600 | 29.045 | 0.1041298 | sum | 7 | summer | NA | NA | NA | 0.84000 | 7 | Table 1 | 247 | 0 | Coral_N aggregated over entire sampling year | Belt | 21 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6314239 | 302.69 | 0.000000 |
| 778 | EI0854 | CD108 | SI186 | 0.0000000 | % | NA | Table 1 | 2009 | 0 | 0 | Table 1 | Surin Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 9.454450 | 97.87704 | 9.454450 | 97.87704 | GoogleMaps Surin Islands | NA | NA | NA | Indian Ocean | 29.04500 | 29.0450 | NA | 7 | 7 | 28.96600 | 29.045 | 0.1041298 | sum | 7 | summer | NA | NA | NA | 0.84000 | 7 | Table 1 | 247 | 0 | Coral_N aggregated over entire sampling year | Belt | 21 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6314239 | 302.69 | 0.000000 |
| 779 | EI0855 | CD108 | SI186 | 8.5000000 | % | NA | Table 1 | 2009 | 0 | 0 | Table 1 | Surin Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 9.454450 | 97.87704 | 9.454450 | 97.87704 | GoogleMaps Surin Islands | NA | NA | NA | Indian Ocean | 29.04500 | 29.0450 | NA | 7 | 7 | 28.96600 | 29.045 | 0.1041298 | sum | 7 | summer | NA | NA | NA | 0.84000 | 7 | Table 1 | 247 | 0 | Coral_N aggregated over entire sampling year | Belt | 21 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6314239 | 302.69 | 0.000000 |
| 780 | EI0856 | CD108 | SI186 | 22.3000000 | % | NA | Table 1 | 2010 | Nov | Nov | Table 1 | Surin Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 9.454450 | 97.87704 | 9.454450 | 97.87704 | GoogleMaps Surin Islands | NA | NA | NA | Indian Ocean | 28.39300 | 28.3930 | NA | 11 | 11 | 29.21600 | 29.278 | 0.3689280 | aut | 11 | fall | NA | NA | NA | 0.72000 | 6 | Table 1 | 292 | 0 | Coral_N aggregated over entire sampling year | Belt | 18 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4653473 | 302.69 | 11.891382 |
| 781 | EI0857 | CD108 | SI186 | 0.3000000 | % | NA | Table 1 | 2010 | Nov | Nov | Table 1 | Surin Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 9.454450 | 97.87704 | 9.454450 | 97.87704 | GoogleMaps Surin Islands | NA | NA | NA | Indian Ocean | 28.39300 | 28.3930 | NA | 11 | 11 | 29.21600 | 29.278 | 0.3689280 | aut | 11 | fall | NA | NA | NA | 0.72000 | 6 | Table 1 | 292 | 0 | Coral_N aggregated over entire sampling year | Belt | 18 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4653473 | 302.69 | 11.891382 |
| 782 | EI0858 | CD108 | SI186 | 9.2000000 | % | NA | Table 1 | 2010 | Nov | Nov | Table 1 | Surin Island, Andaman Sea | Material and Methods p57 | Eastern Indian Ocean | Southeast Asia | 9.454450 | 97.87704 | 9.454450 | 97.87704 | GoogleMaps Surin Islands | NA | NA | NA | Indian Ocean | 28.39300 | 28.3930 | NA | 11 | 11 | 29.21600 | 29.278 | 0.3689280 | aut | 11 | fall | NA | NA | NA | 0.72000 | 6 | Table 1 | 292 | 0 | Coral_N aggregated over entire sampling year | Belt | 18 | 20.0000 | 2.00 | 40.0000 | Material and Methods p57 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4653473 | 302.69 | 11.891382 |
| 783 | EI0859 | CD109 | SI187 | 12.2500000 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Vethalai, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 784 | EI0860 | CD109 | SI187 | 17.9166670 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | T Nagar, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 785 | EI0861 | CD109 | SI187 | 20.6250000 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Shooting thidal, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 786 | EI0862 | CD109 | SI187 | 28.5416670 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Mandapam, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 787 | EI0863 | CD109 | SI187 | 43.3333330 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Mandapam jetty, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 788 | EI0864 | CD109 | SI187 | 15.2083330 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Koilvadi, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 789 | EI0865 | CD109 | SI187 | 8.3333330 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Pampan, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 790 | EI0866 | CD109 | SI187 | 7.7083330 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Thangachimadam, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 791 | EI0867 | CD109 | SI187 | 9.7916670 | % | NA | Figure 2 | 2009 | Apr-Sep | Apr-Sep | Materials and Methods p813 | Rameswaram north, Palk Bay | Figure 2 | Eastern Indian Ocean | Central Indian | 9.534950 | 79.24993 | 9.534950 | 79.24993 | GoogleMaps Palk Bay | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Indian Ocean | 29.09650 | 28.7540 | 0.6458702 | 4 | 9 | 28.69700 | 28.635 | 0.1546215 | multi | 4 | spring | NA | NA | NA | 0.48000 | 2 | Materials and Methods p814 | 4256 | 1 | Coral_N aggregated from whole study | Belt | 6 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p814 | Material and Methods p814 says “9 locations (18 sites…” so assumed 2 sites per location and 3 transects per site | 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “white spot” classified as WPx | 1.5328674 | 303.72 | 0.000000 |
| 792 | EI0868 | CD110 | SI188 | 12.3076920 | % | 0.9615385 | Figure 3 | 2016 | Sep | Sep | Materials and Methods Sampling sites and environmental parameters p194 | North Bali Island | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -8.140280 | 114.65485 | -8.140280 | 114.65485 | GoogleMaps Selini Beach Bali | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.10800 | 28.1080 | NA | 9 | 9 | 29.21767 | 29.210 | 0.2365939 | spr | 3 | spring | 1.6654335 | NA | NA | 0.06000 | 1 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | massive Porites species | Belt | 3 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 302.23 | 30.004151 |
| 793 | EI0869 | CD110 | SI188 | 2.3076920 | % | 0.1923077 | Figure 3 | 2016 | Sep | Sep | Materials and Methods Sampling sites and environmental parameters p194 | North Bali Island | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -8.140280 | 114.65485 | -8.140280 | 114.65485 | GoogleMaps Selini Beach Bali | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.10800 | 28.1080 | NA | 9 | 9 | 29.21767 | 29.210 | 0.2365939 | spr | 3 | spring | 0.3330867 | NA | NA | 0.06000 | 1 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | massive Porites species | Belt | 3 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 302.23 | 30.004151 |
| 794 | EI0870 | CD110 | SI188 | 46.9230770 | % | 1.7307692 | Figure 3 | 2016 | Sep | Sep | Materials and Methods Sampling sites and environmental parameters p194 | North Bali Island | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -8.140280 | 114.65485 | -8.140280 | 114.65485 | GoogleMaps Selini Beach Bali | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.10800 | 28.1080 | NA | 9 | 9 | 29.21767 | 29.210 | 0.2365939 | spr | 3 | spring | 2.9977802 | NA | NA | 0.06000 | 1 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | massive Porites species | Belt | 3 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 302.23 | 30.004151 |
| 795 | EI0871 | CD110 | SI188 | 2.3076920 | % | 0.1923077 | Figure 3 | 2016 | Sep | Sep | Materials and Methods Sampling sites and environmental parameters p194 | North Bali Island | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -8.140280 | 114.65485 | -8.140280 | 114.65485 | GoogleMaps Selini Beach Bali | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.10800 | 28.1080 | NA | 9 | 9 | 29.21767 | 29.210 | 0.2365939 | spr | 3 | spring | 0.3330867 | NA | NA | 0.06000 | 1 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | massive Porites species | Belt | 3 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 302.23 | 30.004151 |
| 796 | EI0872 | CD110 | SI188 | 76.9230770 | % | 0.9615385 | Figure 3 | 2016 | Sep | Sep | Materials and Methods Sampling sites and environmental parameters p194 | North Bali Island | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -8.140280 | 114.65485 | -8.140280 | 114.65485 | GoogleMaps Selini Beach Bali | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.10800 | 28.1080 | NA | 9 | 9 | 29.21767 | 29.210 | 0.2365939 | spr | 3 | spring | 1.6654335 | NA | NA | 0.06000 | 1 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | massive Porites species | Belt | 3 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 302.23 | 30.004151 |
| 797 | EI0873 | CD110 | SI188 | 90.5769230 | % | 0.7692308 | Figure 3 | 2016 | Sep | Sep | Materials and Methods Sampling sites and environmental parameters p194 | North Bali Island | Figure 1 | Coral Triangle & SE Asia | Southeast Asia | -8.140280 | 114.65485 | -8.140280 | 114.65485 | GoogleMaps Selini Beach Bali | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 3 | Pacific Ocean | 28.10800 | 28.1080 | NA | 9 | 9 | 29.21767 | 29.210 | 0.2365939 | spr | 3 | spring | 1.3323468 | NA | NA | 0.06000 | 1 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | massive Porites species | Belt | 3 | 10.0000 | 2.00 | 20.0000 | Materials and Methods Sampling sites and environmental parameters p194 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5814209 | 302.23 | 30.004151 |
| 798 | EI0874 | CD111 | SI189 | 0.6875000 | % | 0.25 | Figure 3 | 2005 | 0 | 0 | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 28.98800 | 28.9880 | NA | 7 | 7 | 28.98433 | 28.988 | 0.3525143 | sum | 7 | summer | 2.5980760 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4714050 | 301.54 | 1.108560 |
| 799 | EI0875 | CD111 | SI189 | 9.8125000 | % | 1.75 | Figure 3 | 2006 | Jan-May | Jan-May | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 26.72720 | 26.1850 | 0.6833574 | 1 | 5 | 28.51000 | 28.395 | 0.2167377 | multi | 1 | winter | 18.1865330 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2760696 | 301.54 | 12.398520 |
| 800 | EI0876 | CD111 | SI189 | 4.1875000 | % | 0.8125 | Figure 3 | 2006 | Jun-Dec | Jun-Dec | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 28.60829 | 29.4150 | 0.6229745 | 6 | 12 | 28.51000 | 28.395 | 0.2167377 | multi | 6 | summer | 8.4437480 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6828613 | 301.54 | 12.398520 |
| 801 | EI0877 | CD111 | SI189 | 0.2500000 | % | 0.125 | Figure 3 | 2007 | 0 | 0 | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 28.81000 | 28.8100 | NA | 7 | 7 | 28.72200 | 28.810 | 0.2093630 | sum | 7 | summer | 1.2990380 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2164307 | 301.54 | 3.508573 |
| 802 | EI0878 | CD111 | SI189 | 0.4375000 | % | 0.25 | Figure 3 | 2008 | 0 | 0 | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 28.45300 | 28.4530 | NA | 7 | 7 | 28.49633 | 28.453 | 0.5063926 | sum | 7 | summer | 2.5980760 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5399780 | 301.54 | 0.000000 |
| 803 | EI0879 | CD111 | SI189 | 0.5625000 | % | 0.3125 | Figure 3 | 2009 | 0 | 0 | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 28.52000 | 28.5200 | NA | 7 | 7 | 28.37167 | 28.520 | 0.4225026 | sum | 7 | summer | 3.2475950 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2467728 | 301.54 | 0.000000 |
| 804 | EI0880 | CD111 | SI189 | 0.3125000 | % | 0.125 | Figure 3 | 2010 | 0 | 0 | Figure 3 | US Virgin Islands | Methods | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.920320 | -64.95859 | 18.920320 | -64.95859 | GoogleMaps US Virgin Islands | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 108 | Atlantic Ocean | 29.10500 | 29.1050 | NA | 7 | 7 | 29.16267 | 29.105 | 0.4016176 | sum | 7 | summer | 1.2990380 | NA | NA | 1.08000 | 18 | Methods | 9989 | 1 | coral_n aggregated over whole study | Line | 108 | 10.0000 | 1.00 | 10.0000 | Methods | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.0799866 | 301.54 | 0.000000 |
| 805 | EI0881 | CD112 | SI190 | 0.0000000 | % | 9.76E-02 | Figure 6 | 1994 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 22 | Atlantic Ocean | 29.25500 | 29.2550 | NA | 7 | 7 | 29.13600 | 29.255 | 0.4116106 | sum | 7 | summer | 0.4578046 | NA | NA | 4.40000 | 22 | Figure 6 | NA | NA | NA | Belt | 22 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8582153 | 302.71 | 0.000000 |
| 806 | EI0882 | CD112 | SI190 | 0.8695652 | % | 0.14196983 | Figure 6 | 1995 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 15 | Atlantic Ocean | 29.64500 | 29.6450 | NA | 7 | 7 | 29.35600 | 29.645 | 0.5694499 | sum | 7 | summer | 0.5498468 | NA | NA | 3.00000 | 15 | Figure 6 | NA | NA | NA | Belt | 15 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4735794 | 302.71 | 0.000000 |
| 807 | EI0883 | CD112 | SI190 | 0.9130435 | % | 0.17524401 | Figure 6 | 1996 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 11 | Atlantic Ocean | 29.62300 | 29.6230 | NA | 7 | 7 | 29.35300 | 29.623 | 0.5565070 | sum | 7 | summer | 0.5812186 | NA | NA | 2.20000 | 11 | Figure 6 | NA | NA | NA | Belt | 11 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8971558 | 302.71 | 0.000000 |
| 808 | EI0884 | CD112 | SI190 | 0.0000000 | % | 0.24401065 | Figure 6 | 1997 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 6 | Atlantic Ocean | 30.21300 | 30.2130 | NA | 7 | 7 | 29.89767 | 30.213 | 0.9980865 | sum | 7 | summer | 0.5977016 | NA | NA | 1.20000 | 6 | Figure 6 | NA | NA | NA | Belt | 6 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3157501 | 302.71 | 0.000000 |
| 809 | EI0885 | CD112 | SI190 | 0.5826087 | % | 0.12644188 | Figure 6 | 1998 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 12 | Atlantic Ocean | 30.12800 | 30.1280 | NA | 7 | 7 | 29.92967 | 30.128 | 0.7329106 | sum | 7 | summer | 0.4380075 | NA | NA | 2.40000 | 12 | Figure 6 | NA | NA | NA | Belt | 12 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1171570 | 302.71 | 4.505706 |
| 810 | EI0886 | CD112 | SI190 | 0.1130435 | % | 0.19299024 | Figure 6 | 2001 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 9 | Atlantic Ocean | 29.31500 | 29.3150 | NA | 7 | 7 | 29.18267 | 29.315 | 0.6664279 | sum | 7 | summer | 0.5789707 | NA | NA | 1.80000 | 9 | Figure 6 | NA | NA | NA | Belt | 9 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6596680 | 302.71 | 0.000000 |
| 811 | EI0887 | CD112 | SI190 | 0.4217391 | % | 0.12200532 | Figure 6 | 2002 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 19 | Atlantic Ocean | 29.57000 | 29.5700 | NA | 7 | 7 | 29.28100 | 29.570 | 0.8463531 | sum | 7 | summer | 0.5318089 | NA | NA | 3.80000 | 19 | Figure 6 | NA | NA | NA | Belt | 19 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9699860 | 302.71 | 0.000000 |
| 812 | EI0888 | CD112 | SI190 | 0.2000000 | % | 0.14862467 | Figure 6 | 2004 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 15 | Atlantic Ocean | 30.03000 | 30.0300 | NA | 7 | 7 | 29.70267 | 30.030 | 0.6917527 | sum | 7 | summer | 0.5756209 | NA | NA | 3.00000 | 15 | Figure 6 | NA | NA | NA | Belt | 15 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4207153 | 302.71 | 0.000000 |
| 813 | EI0889 | CD112 | SI190 | 0.0000000 | % | 9.76E-02 | Figure 6 | 2005 | 0 | 0 | Figure 6 | Florida Keys National Marine Sanctuary | Materials and Methods White plague type ii data collection | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.574000 | -83.13982 | 24.574000 | -83.13982 | GoogleMaps Florida Keys National Marine Sanctuary | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 22 | Atlantic Ocean | 29.61300 | 29.6130 | NA | 7 | 7 | 29.48634 | 29.613 | 0.9712149 | sum | 7 | summer | 0.4578046 | NA | NA | 4.40000 | 22 | Figure 6 | NA | NA | NA | Belt | 22 | 200.0000 | 1.00 | 200.0000 | Materials and Methods White plague type ii data collection | NA | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5742798 | 302.71 | 0.000000 |
| 814 | EI0890 | CD113 | SI191 | 30.4000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1994 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.37800 | 29.3780 | NA | 7 | 7 | 29.27267 | 29.378 | 0.4151469 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 92 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.9589157 | 302.79 | 1.090005 |
| 815 | EI0891 | CD113 | SI191 | 50.7000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1995 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.71300 | 29.7130 | NA | 7 | 7 | 29.40867 | 29.713 | 0.5594703 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 69 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7863998 | 302.79 | 0.000000 |
| 816 | EI0892 | CD113 | SI191 | 57.7000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1996 | Oct | Oct | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.00500 | 28.0050 | NA | 10 | 10 | 29.30533 | 29.528 | 0.5508550 | aut | 10 | fall | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 52 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7700195 | 302.79 | 0.000000 |
| 817 | EI0893 | CD113 | SI191 | 60.9000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1997 | Jun | Jun | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 28.83500 | 28.8350 | NA | 6 | 6 | 29.94600 | 30.268 | 0.9900823 | sum | 6 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 46 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3528290 | 302.79 | 0.000000 |
| 818 | EI0894 | CD113 | SI191 | 64.3000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1997 | Sep | Sep | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.73800 | 29.7380 | NA | 9 | 9 | 29.94600 | 30.268 | 0.9900823 | aut | 9 | fall | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 42 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4221497 | 302.79 | 8.314264 |
| 819 | EI0895 | CD113 | SI191 | 62.1000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1998 | May | May | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 26.72300 | 26.7230 | NA | 5 | 5 | 30.05700 | 30.303 | 0.7259636 | spr | 5 | spring | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 29 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.0099945 | 302.79 | 8.314264 |
| 820 | EI0896 | CD113 | SI191 | 71.4000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1998 | Sep | Sep | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.59300 | 29.5930 | NA | 9 | 9 | 30.05700 | 30.303 | 0.7259636 | aut | 9 | fall | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 21 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4550018 | 302.79 | 6.225684 |
| 821 | EI0897 | CD113 | SI191 | 44.4000000 | % | NA | Results Disease prevalence and incidence rate p9 | 1999 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.45300 | 29.4530 | NA | 7 | 7 | 29.45433 | 29.453 | 0.8800009 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 9 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4550018 | 302.79 | 6.225684 |
| 822 | EI0898 | CD113 | SI191 | 33.3000000 | % | NA | Results Disease prevalence and incidence rate p9 | 2000 | Dec | Dec | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 24.94300 | 24.9430 | NA | 12 | 12 | 29.36533 | 29.813 | 0.8589678 | win | 12 | winter | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 3 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1993027 | 302.79 | 0.000000 |
| 823 | EI0899 | CD113 | SI191 | 0.0000000 | % | NA | Results Disease prevalence and incidence rate p9 | 2001 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.35500 | 29.3550 | NA | 7 | 7 | 29.25034 | 29.355 | 0.7008858 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 3 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6314239 | 302.79 | 0.000000 |
| 824 | EI0900 | CD113 | SI191 | 50.0000000 | % | NA | Results Disease prevalence and incidence rate p9 | 2002 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.60800 | 29.6080 | NA | 7 | 7 | 29.33134 | 29.608 | 0.8927529 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 2 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.7953568 | 302.79 | 1.409982 |
| 825 | EI0901 | CD113 | SI191 | 0.0000000 | % | NA | Results Disease prevalence and incidence rate p9 | 2003 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 29.54000 | 29.5400 | NA | 7 | 7 | 29.46200 | 29.540 | 0.6037899 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 1 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.3203430 | 302.79 | 0.000000 |
| 826 | EI0902 | CD113 | SI191 | 50.0000000 | % | NA | Results Disease prevalence and incidence rate p9 | 2004 | Jul | Jul | Material and Methods p7 | Eastern Dry Rocks Reef Florida Keys Marine Sanctuary | Material and Methods p7 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.460283 | -81.84305 | 24.460283 | -81.84305 | Material and Methods p7, GoogleMaps | NA | NA | NA | Atlantic Ocean | 30.08000 | 30.0800 | NA | 7 | 7 | 29.74267 | 30.080 | 0.7135448 | sum | 7 | summer | NA | NA | NA | 13.50000 | 1 | Material and Methods p7 | 2 | 0 | NA | Quadrat | 36 | 0.7500 | 0.25 | 0.1875 | Material and Methods p7 | Quadrats contiguous to create one large sample area; for some reason this math doesn’t add up… | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3414307 | 302.79 | 0.000000 |
| 827 | EI0903 | CD114 | SI192 | 21.7000000 | % | NA | Results | 2015 | Oct-Nov | Oct-Nov | Methods Disease prevalence surveys, lesion progression monitoring and sampling | Luminao Reef, Guam | Results | Western Pacific | Micronesia | 16.675260 | 144.08563 | 16.675260 | 144.08563 | GoogleMaps Guam | NA | NA | NA | Pacific Ocean | 28.95300 | 28.9530 | 0.2828424 | 10 | 11 | 29.29867 | 29.353 | 0.1634204 | aut | 10 | fall | NA | NA | NA | 0.06000 | 1 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | 53 | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NA | 0.5971375 | 302.41 | 0.000000 |
| 828 | EI0904 | CD114 | SI193 | 0.0000000 | % | NA | Results | 2011 | Jun | Jun | Methods Disease prevalence surveys, lesion progression monitoring and sampling | Philippines | Results | Coral Triangle & SE Asia | Southeast Asia | 11.208060 | 123.73960 | 11.208060 | 123.73960 | GoogleMaps Bantayan Island | NA | NA | NA | Pacific Ocean | 29.51000 | 29.5100 | NA | 6 | 6 | 29.25433 | 29.240 | 0.2488106 | sum | 6 | summer | NA | NA | NA | 1.08000 | 18 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | NA | Belt | 54 | 20.0000 | 1.00 | 20.0000 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NA | 0.6021194 | 302.69 | 6.459946 |
| 829 | EI0905 | CD114 | SI193 | 0.0000000 | % | NA | Results | 2015 | Apr | Apr | Methods Disease prevalence surveys, lesion progression monitoring and sampling | Philippines | Results | Coral Triangle & SE Asia | Southeast Asia | 11.208060 | 123.73960 | 11.208060 | 123.73960 | GoogleMaps Bantayan Island | NA | NA | NA | Pacific Ocean | 28.20000 | 28.2000 | NA | 4 | 4 | 29.76200 | 29.345 | 0.4494139 | spr | 4 | spring | NA | NA | NA | 1.08000 | 18 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | NA | Belt | 54 | 20.0000 | 1.00 | 20.0000 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NA | 0.3374863 | 302.69 | 0.000000 |
| 830 | EI0906 | CD114 | SI194 | 0.0000000 | % | NA | Results | 2018 | May | May | Methods Disease prevalence surveys, lesion progression monitoring and sampling | Palau | Results | Western Pacific | Micronesia | 8.401070 | 134.57791 | 8.401070 | 134.57791 | GoogleMaps Palau | NA | NA | NA | Pacific Ocean | 30.04000 | 30.0400 | NA | 5 | 5 | 29.43533 | 29.508 | 0.4504181 | spr | 5 | spring | NA | NA | NA | 0.06000 | 1 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NA | 0.8250275 | 302.41 | 8.115692 |
| 831 | EI0907 | CD114 | SI195 | 0.0000000 | % | NA | Results | 2017 | Sep | Sep | Methods Disease prevalence surveys, lesion progression monitoring and sampling | Maldives | Results | Western Indian Ocean | Central Indian | 7.999790 | 72.69305 | 7.999790 | 72.69305 | GoogleMaps Maldives | NA | NA | NA | Indian Ocean | 28.28800 | 28.2880 | NA | 9 | 9 | 28.83767 | 28.790 | 0.2716551 | aut | 9 | fall | NA | NA | NA | 0.06000 | 1 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NA | 1.7156982 | 303.15 | 0.000000 |
| 832 | EI0908 | CD114 | SI196 | 0.0000000 | % | NA | Results | 2018 | Mar | Mar | Methods Disease prevalence surveys, lesion progression monitoring and sampling | Reunion | Results | Western Indian Ocean | West Indian | -19.071860 | 55.17569 | -19.071860 | 55.17569 | GoogleMaps Reunion Island | NA | NA | NA | Indian Ocean | 28.12000 | 28.1200 | NA | 3 | 3 | 28.31100 | 28.480 | 0.8364045 | aut | 9 | fall | NA | NA | NA | 0.06000 | 1 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | NA | Belt | 3 | 20.0000 | 1.00 | 20.0000 | Methods Disease prevalence surveys, lesion progression monitoring and sampling | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NA | 0.2735672 | 301.12 | 5.499953 |
| 833 | EI0909 | CD115 | SI197 | 8.0000000 | % | NA | Results p71 | 2009 | Jan | Jan | Results p71 | Shingle Island | Materials and Methods p70 | Eastern Indian Ocean | Central Indian | 9.241760 | 79.23592 | 9.241760 | 79.23592 | GoogleMaps Shingle Island | NA | NA | NA | Indian Ocean | 27.18500 | 27.1850 | NA | 1 | 1 | 28.69700 | 28.635 | 0.1546215 | win | 1 | winter | NA | NA | NA | 0.24000 | 1 | Figure 1 | 2910 | 1 | Coral_N aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p70 | NA | 4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7635880 | 303.56 | 0.000000 |
| 834 | EI0910 | CD115 | SI197 | 26.9000000 | % | NA | Results p71 | 2009 | Dec | Dec | Results p71 | Shingle Island | Materials and Methods p70 | Eastern Indian Ocean | Central Indian | 9.241760 | 79.23592 | 9.241760 | 79.23592 | GoogleMaps Shingle Island | NA | NA | NA | Indian Ocean | 28.36300 | 28.3630 | NA | 12 | 12 | 28.69700 | 28.635 | 0.1546215 | win | 12 | winter | NA | NA | NA | 0.24000 | 1 | Figure 1 | 2910 | 1 | Coral_N aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p70 | NA | 4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.7785645 | 303.56 | 0.000000 |
| 835 | EI0911 | CD115 | SI197 | 41.9000000 | % | NA | Results p71 | 2010 | Dec | Dec | Results p71 | Shingle Island | Materials and Methods p70 | Eastern Indian Ocean | Central Indian | 9.241760 | 79.23592 | 9.241760 | 79.23592 | GoogleMaps Shingle Island | NA | NA | NA | Indian Ocean | 27.59500 | 27.5950 | NA | 12 | 12 | 28.84533 | 28.833 | 0.4036409 | win | 12 | winter | NA | NA | NA | 0.24000 | 1 | Figure 1 | 2910 | 1 | Coral_N aggregated from whole study | Belt | 3 | 20.0000 | 4.00 | 80.0000 | Materials and Methods p70 | NA | 4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4371338 | 303.56 | 4.147088 |
| 836 | EI0912 | CD116 | SI198 | 0.6600000 | % | NA | Table 1 | 2002 | Jun-Jul | Jun-Jul | Materials and Methods Surveys p34 | Lee Stocking Island, Bahamas | Materials and Methods Surveys p34 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 23.773530 | -76.09886 | 23.773530 | -76.09886 | GoogleMaps Lee Stocking Island | NA | NA | NA | Atlantic Ocean | 28.28050 | 28.2805 | 0.7106417 | 6 | 7 | 28.65133 | 28.783 | 0.8155109 | sum | 6 | summer | NA | NA | NA | 9.42000 | 10 | Materials and Methods Surveys p34 | 11092 | 1 | NA | Circle | 150 | 20.0000 | NA | 314.0000 | Materials and Methods Surveys p34 | length is diameter | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3335495 | 302.24 | 0.000000 |
| 837 | EI0913 | CD116 | SI198 | 0.6100000 | % | NA | Table 1 | 2003 | Jun-Jul | Jun-Jul | Materials and Methods Surveys p34 | Lee Stocking Island, Bahamas | Materials and Methods Surveys p34 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 23.773530 | -76.09886 | 23.773530 | -76.09886 | GoogleMaps Lee Stocking Island | NA | NA | NA | Atlantic Ocean | 28.38800 | 28.3880 | 0.3181972 | 6 | 7 | 28.58867 | 28.613 | 0.4140364 | sum | 6 | summer | NA | NA | NA | 10.36200 | 10 | Materials and Methods Surveys p34 | 13973 | 1 | NA | Circle | 165 | 20.0000 | NA | 314.0000 | Materials and Methods Surveys p34 | length is diameter | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.1700134 | 302.24 | 1.052847 |
| 838 | EI0914 | CD117 | SI199 | 0.3000000 | % | NA | Table 2 | 2008 | Jul-Aug, Oct-Nov | Jul-Aug, Oct-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | NA | Pacific Ocean | 28.17280 | 28.3730 | 0.1796198 | 7 | 11 | 27.96367 | 28.043 | 0.2795733 | multi | 7 | summer | NA | NA | NA | 11.80000 | 12 | Table 1 | 51444 | 1 | NA | Belt | 59 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “Discoloration necrosis” classified as Pigmentation Response | 0.3535919 | 302.10 | 0.000000 |
| 839 | EI0915 | CD117 | SI199 | 0.2700000 | % | NA | Table 3 | 2009 | Jul, Oct-Nov | Jul-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | Simplified month sampling period for data analysis | Pacific Ocean | 29.41940 | 29.3100 | 0.2592918 | 7 | 11 | 29.07634 | 29.133 | 0.2547710 | multi | 7 | summer | NA | NA | NA | 2.00000 | 12 | Table 1 | NA | 1 | NA | Belt | 40 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414612 | 302.10 | 0.000000 |
| 840 | EI0916 | CD117 | SI199 | 3.4400000 | % | NA | Table 3 | 2009 | Jul, Oct-Nov | Jul-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | Simplified month sampling period for data analysis | Pacific Ocean | 29.41940 | 29.3100 | 0.2592918 | 7 | 11 | 29.07634 | 29.133 | 0.2547710 | multi | 7 | summer | NA | NA | NA | 2.00000 | 12 | Table 1 | NA | 1 | NA | Belt | 40 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414612 | 302.10 | 0.000000 |
| 841 | EI0917 | CD117 | SI199 | 3.0100000 | % | NA | Table 3 | 2009 | Jul, Oct-Nov | Jul-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | Simplified month sampling period for data analysis | Pacific Ocean | 29.41940 | 29.3100 | 0.2592918 | 7 | 11 | 29.07634 | 29.133 | 0.2547710 | multi | 7 | summer | NA | NA | NA | 2.00000 | 12 | Table 1 | NA | 1 | NA | Belt | 40 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414612 | 302.10 | 0.000000 |
| 842 | EI0918 | CD117 | SI199 | 0.5100000 | % | NA | Table 3 | 2009 | Jul, Oct-Nov | Jul-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | Simplified month sampling period for data analysis | Pacific Ocean | 29.41940 | 29.3100 | 0.2592918 | 7 | 11 | 29.07634 | 29.133 | 0.2547710 | multi | 7 | summer | NA | NA | NA | 2.00000 | 12 | Table 1 | NA | 1 | NA | Belt | 40 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414612 | 302.10 | 0.000000 |
| 843 | EI0919 | CD117 | SI199 | 1.1800000 | % | NA | Table 3 | 2009 | Jul, Oct-Nov | Jul-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | Simplified month sampling period for data analysis | Pacific Ocean | 29.41940 | 29.3100 | 0.2592918 | 7 | 11 | 29.07634 | 29.133 | 0.2547710 | multi | 7 | summer | NA | NA | NA | 2.00000 | 12 | Table 1 | NA | 1 | NA | Belt | 40 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8414612 | 302.10 | 0.000000 |
| 844 | EI0920 | CD117 | SI199 | 0.0800000 | % | NA | Table 3 | 2009 | Jul, Oct-Nov | Jul-Nov | Materials and Methods Disease spatial and temporal patterns p90 | Palmyra Atoll | Table 2 | Western Pacific | Micronesia | 5.866667 | -162.10000 | 5.866667 | -162.10000 | Materials and Methods Study site p90, GoogleMaps | NA | NA | Simplified month sampling period for data analysis | Pacific Ocean | 29.41940 | 29.3100 | 0.2592918 | 7 | 11 | 29.07634 | 29.133 | 0.2547710 | multi | 7 | summer | NA | NA | NA | 2.00000 | 12 | Table 1 | NA | 1 | NA | Belt | 40 | 50.0000 | 4.00 | 200.0000 | Materials and Methods Disease spatial and temporal patterns p91 | Transect diameter changes halfway down transect, took average of widths | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | “Discoloration necrosis” classified as Pigmentation Response | 0.8414612 | 302.10 | 0.000000 |
| 845 | EI0921 | CD118 | SI200 | 59.0000000 | % | 7.6 | Results Coral lesions in response to biotic factors Pigmentation response p80 | 2015 | May | May | Materials and Methods Survey technique p79 | Kish Island | Figure 1 | Western Indian Ocean | Middle East | 26.533333 | 53.96667 | 26.533333 | 53.96667 | Materials and Methods Study area p78 | NA | NA | NA | Indian Ocean | 28.23500 | 28.2350 | NA | 5 | 5 | 31.87133 | 31.828 | 1.5354585 | spr | 5 | spring | NA | NA | NA | 0.48000 | 4 | Material and Methods Survey technique p78 | 474 | 1 | NA | Belt | 12 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Survey technique p79 | Transect width averaged - real width between 1-3m | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3114014 | 306.40 | 0.000000 |
| 846 | EI0922 | CD118 | SI200 | 40.0000000 | % | 4.8 | Results Coral lesions in response to biotic factors Pigmentation response p80 | 2015 | May | May | Materials and Methods Survey technique p79 | Kish Island | Figure 1 | Western Indian Ocean | Middle East | 26.533333 | 53.96667 | 26.533333 | 53.96667 | Materials and Methods Study area p78 | NA | NA | NA | Indian Ocean | 28.23500 | 28.2350 | NA | 5 | 5 | 31.87133 | 31.828 | 1.5354585 | spr | 5 | spring | NA | NA | NA | 0.48000 | 4 | Material and Methods Survey technique p78 | 474 | 1 | NA | Belt | 12 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Survey technique p79 | Transect width averaged - real width between 1-3m | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3114014 | 306.40 | 0.000000 |
| 847 | EI0923 | CD118 | SI200 | 8.0000000 | % | 2.3 | Result Coral lesions in response to biotic factors Disease p80 | 2015 | May | May | Materials and Methods Survey technique p79 | Kish Island | Figure 1 | Western Indian Ocean | Middle East | 26.533333 | 53.96667 | 26.533333 | 53.96667 | Materials and Methods Study area p78 | NA | NA | NA | Indian Ocean | 28.23500 | 28.2350 | NA | 5 | 5 | 31.87133 | 31.828 | 1.5354585 | spr | 5 | spring | NA | NA | NA | 0.48000 | 4 | Material and Methods Survey technique p78 | 474 | 1 | NA | Belt | 12 | 20.0000 | 2.00 | 40.0000 | Materials and Methods Survey technique p79 | Transect width averaged - real width between 1-3m | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3114014 | 306.40 | 0.000000 |
| 848 | EI0924 | CD119 | SI201 | 1.2000000 | % | NA | Results p77 | 2004 | May | May | Materials and Methods p76 | shallow barrier reef Dos Masquises Sur, National Park of Los Roques, Venezuela | Materials and Methods p76 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 13.425100 | -66.89277 | 13.425100 | -66.89277 | GoogleMaps Dos Mosquises Sur | NA | NA | NA | Atlantic Ocean | 27.52800 | 27.5280 | NA | 5 | 5 | 28.01667 | 27.880 | 0.4075644 | spr | 5 | spring | NA | NA | NA | 0.25500 | 2 | Materials and Methods p76 | 1266 | 1 | NA | Belt-Quadrat | 5 | 25.0000 | 2.00 | 55.0000 | Materials and Methods p76 | Sampling done in each site differently, data presented here for A palmata-dominated site sampling methods, plot area added 5m^2 for the area of the A cervicornis-dominated site sample area | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | NA | 0.7953567 | 301.46 | 7.689955 |
| 849 | EI0925 | CD119 | SI201 | 2.6000000 | % | NA | Results p77 | 2004 | May | May | Materials and Methods p76 | shallow fringing reef Dos Masquises Sur, National Park of Los Roques, Venezuela | Materials and Methods p76 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 13.425100 | -66.89277 | 13.425100 | -66.89277 | GoogleMaps Dos Mosquises Sur | NA | NA | NA | Atlantic Ocean | 27.52800 | 27.5280 | NA | 5 | 5 | 28.01667 | 27.880 | 0.4075644 | spr | 5 | spring | NA | NA | NA | 0.15000 | 1 | Materials and Methods p76 | 513 | 1 | NA | Belt | 3 | 25.0000 | 2.00 | 50.0000 | Materials and Methods p76 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | NA | 0.7953567 | 301.46 | 7.689955 |
| 850 | EI0926 | CD119 | SI201 | 9.0000000 | % | NA | Results p78 | 2004 | May | May | Materials and Methods p76 | deep fringing reef Dos Masquises Sur, National Park of Los Roques, Venezuela | Materials and Methods p76 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 13.425100 | -66.89277 | 13.425100 | -66.89277 | GoogleMaps Dos Mosquises Sur | NA | NA | NA | Atlantic Ocean | 27.52800 | 27.5280 | NA | 5 | 5 | 28.01667 | 27.880 | 0.4075644 | spr | 5 | spring | NA | NA | NA | 0.07500 | 1 | Materials and Methods p76 | 91 | 1 | NA | Line | 3 | 25.0000 | 1.00 | 25.0000 | Materials and Methods p76 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | NA | 0.7953567 | 301.46 | 7.689955 |
| 851 | EI0927 | CD120 | SI202 | 1.6000000 | % | NA | Results and Disucssions p188 | 2005 | Mar | Mar | Results and Disucssions p188 | Bocas del Toro, Panama | Results and Disucssions p188 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 9.543820 | -82.29074 | 9.543820 | -82.29074 | GoogleMaps Bocas del Toro | NA | NA | NA | Atlantic Ocean | 28.08000 | 28.0800 | NA | 3 | 3 | 28.94333 | 28.800 | 0.2526026 | spr | 3 | spring | NA | NA | NA | 1.80000 | 6 | Results and Disucssions p188 | 23869 | 1 | NA | Belt | 90 | 10.0000 | 2.00 | 20.0000 | Results and Disucssions p188 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | NA | 0.5253372 | 301.58 | 4.837107 |
| 852 | EI0930 | CD122 | SI203 | 2.0000000 | % | NA | Results p27 | 2003 | Aug, Dec | Aug, Dec | Materials and Methods p124 | St John, US Virgin Islands | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.345960 | -64.72921 | 18.335070 | -64.69532 | GoogleMaps St John USVI | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 23 | Atlantic Ocean | 28.48880 | 29.2580 | 0.7108951 | 8 | 12 | 27.95200 | 27.880 | 0.4889915 | multi | 8 | summer | NA | NA | NA | 760.32400 | 29 | Figure 1 | 8473 | 0 | NA | Belt | 29 | NA | NA | 26218.0700 | Materials and Methods p125 | entire sites surveyed, transects only used to divide area into more manageable sections; input here average site size | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | Only most common diseases mentioned (Tissue necrosis and White pox) | 0.3571396 | 301.55 | 0.000000 |
| 853 | EI0931 | CD123 | SI204 | 23.5000000 | % | 11.7 | Discussion Health status of Kure coral communities p18 | 2002 | Sep | Sep | Materials and Methods Benthic surveys p3 | Kure Atoll | Discussion Health status of Kure coral communities p18 | Western Pacific | Polynesia | 28.399940 | -178.29324 | 28.399940 | -178.29324 | GoogleMaps Kure Atoll | NA | NA | NA | Pacific Ocean | 27.48000 | 27.4800 | NA | 9 | 9 | 26.90200 | 27.308 | 1.5202197 | aut | 9 | fall | NA | NA | NA | 0.70000 | 14 | Results Site-specific surveys: video transects p7 | NA | 1 | NA | Belt | 28 | 25.0000 | 1.00 | 25.0000 | Materials and Methods Benthic surveys p3 (Maragos et al. 2004) | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3078613 | 299.93 | 7.092862 |
| 854 | EI0932 | CD123 | SI205 | 7.9000000 | % | 3.1 | Discussion Health status of Kure coral communities p18 | 2002 | Sep | Sep | Materials and Methods Benthic surveys p3 | NWHI (except Kure Atoll) | Discussion Health status of Kure coral communities p18 | Western Pacific | Polynesia | 26.142690 | -170.49279 | 26.142690 | -170.49279 | GoogleMaps Kure Atoll | NA | NA | NA | Pacific Ocean | 27.31500 | 27.3150 | NA | 9 | 9 | 26.63033 | 26.538 | 1.0016966 | aut | 9 | fall | NA | NA | NA | 0.70000 | 14 | Results Site-specific surveys: video transects p7 | NA | 1 | NA | Belt | 28 | 25.0000 | 1.00 | 25.0000 | Materials and Methods Benthic surveys p3 (Maragos et al. 2004) | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8082047 | 300.08 | 1.022845 |
| 855 | EI0933 | CD021 | SI206 | 1.7567570 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 27.00000 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 856 | EI0934 | CD021 | SI206 | 1.9729730 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 27.48649 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 857 | EI0935 | CD021 | SI206 | 2.0540540 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 27.81081 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 858 | EI0936 | CD021 | SI206 | 2.0810810 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 28.22973 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 859 | EI0937 | CD021 | SI206 | 3.0810810 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 28.47297 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 860 | EI0938 | CD021 | SI206 | 4.0000000 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 28.68919 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 861 | EI0939 | CD021 | SI206 | 3.4054050 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 28.77027 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 862 | EI0940 | CD021 | SI206 | 4.8108110 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 28.98649 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 863 | EI0941 | CD021 | SI206 | 5.0540540 | % | NA | Figure 1 | 2009 | May-Sep | May-Sep | Methods Prevalence and incidence of BBD and water temperature p53 | Tague Bay, St. Croix, US Virgin Islands | Methods Prevalence and incidence of BBD and water temperature p53 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 17.764167 | -64.61944 | 17.764167 | -64.61944 | Methods Prevalence and incidence of BBD and water temperature p53, GoogleMaps | 29.12162 | Figure 1 | Prevalence and temperature data extracted using MetaDigitise in Rstudio, n = 1, n = 1 | Atlantic Ocean | 28.32840 | 28.5530 | 0.8002126 | 5 | 9 | 28.47033 | 28.553 | 0.3729362 | multi | 5 | spring | NA | NA | NA | 12.83300 | 1 | Methods Prevalence and incidence of BBD and water temperature p53 | 966 | 0 | NA | Belt | 1 | 313.0000 | 41.00 | 12833.0000 | Methods Prevalence and incidence of BBD and water temperature p53 | No transects, one large sample area | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1192780 | 301.66 | 0.000000 |
| 864 | EI0942 | CD023 | SI207 | 1.1000000 | % | NA | Results p69 | 1999 | 0 | 0 | Results p69 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | NA | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 1.00000 | 50 | Materials and Methods p68 | 2166 | 1 | NA | Belt | 100 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | https://www.researchgate.net/publication/265148106_Agrra_protocols_version_54 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 865 | EI0943 | CD023 | SI207 | 0.1000000 | % | NA | Results p69 | 1999 | 0 | 0 | Results p69 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | NA | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 1.00000 | 50 | Materials and Methods p68 | NA | 1 | NA | Belt | 100 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 866 | EI0944 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 867 | EI0945 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 868 | EI0946 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 869 | EI0947 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 870 | EI0948 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1995 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 28.68300 | 28.6830 | NA | 7 | 7 | 28.47533 | 28.683 | 0.3903919 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.2285461 | 301.79 | 0.000000 |
| 871 | EI0949 | CD023 | SI207 | 2.0512820 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 872 | EI0950 | CD023 | SI207 | 2.8205130 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 873 | EI0951 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 874 | EI0952 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 875 | EI0953 | CD023 | SI207 | 0.0000000 | % | NA | Figure 3 | 1996 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 50 | Atlantic Ocean | 27.96300 | 27.9630 | NA | 7 | 7 | 27.95534 | 27.963 | 0.2186010 | sum | 7 | summer | NA | NA | NA | 15.70000 | 50 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Circle | 50 | 10.0000 | NA | 314.0000 | Materials and Methods p68 | length is radius | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.5310898 | 301.79 | 1.128580 |
| 876 | EI0954 | CD023 | SI207 | 15.1282050 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 877 | EI0955 | CD023 | SI207 | 52.0000000 | % | NA | Results p69 | 1999 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | NA | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 878 | EI0956 | CD023 | SI207 | 19.1025640 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 879 | EI0957 | CD023 | SI207 | 6.2820510 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 880 | EI0958 | CD023 | SI207 | 1.5384620 | % | NA | Figure 3 | 1999 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.37300 | 28.3730 | NA | 7 | 7 | 28.62033 | 28.373 | 0.3984679 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.1535645 | 301.79 | 1.011423 |
| 881 | EI0959 | CD023 | SI207 | 26.1538460 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 882 | EI0960 | CD023 | SI207 | 58.2051280 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 883 | EI0961 | CD023 | SI207 | 18.2051280 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 884 | EI0962 | CD023 | SI207 | 9.3589740 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 885 | EI0963 | CD023 | SI207 | 2.3076920 | % | NA | Figure 3 | 2000 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.04000 | 28.0400 | NA | 7 | 7 | 28.02333 | 28.040 | 0.4452337 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3117905 | 301.79 | 2.081409 |
| 886 | EI0964 | CD023 | SI207 | 24.7435900 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 887 | EI0965 | CD023 | SI207 | 54.4871790 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 888 | EI0966 | CD023 | SI207 | 18.5897440 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 889 | EI0967 | CD023 | SI207 | 11.1538460 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 890 | EI0968 | CD023 | SI207 | 3.7179490 | % | NA | Figure 3 | 2001 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.31000 | 28.3100 | NA | 7 | 7 | 28.35267 | 28.310 | 0.3509506 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.3192978 | 301.79 | 0.000000 |
| 891 | EI0969 | CD023 | SI207 | 15.5128210 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 892 | EI0970 | CD023 | SI207 | 39.2307690 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 893 | EI0971 | CD023 | SI207 | 14.2307690 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 894 | EI0972 | CD023 | SI207 | 16.0256410 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 895 | EI0973 | CD023 | SI207 | 3.7179490 | % | NA | Figure 3 | 2003 | 0 | 0 | Figure 3 | Mona Island | Figure 1 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 18.095390 | -67.89445 | 18.095390 | -67.89445 | GoogleMaps Isla de Mona | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 20 | Atlantic Ocean | 28.07300 | 28.0730 | NA | 7 | 7 | 28.13533 | 28.073 | 0.3625419 | sum | 7 | summer | NA | NA | NA | 0.20000 | 10 | Materials and Methods p68 | NA | 0 | Montastraea annularis sp complex | Belt | 20 | 10.0000 | 1.00 | 10.0000 | AGRRA protocol p14 | NA | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4449768 | 301.79 | 0.000000 |
| 896 | EI0974 | CD005 | SI208 | 2.9600000 | % | NA | Figure 3 | 1998 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 30.11050 | 30.1105 | 0.7318554 | 8 | 9 | 30.05700 | 30.303 | 0.7259636 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4657288 | 302.80 | 8.571403 |
| 897 | EI0975 | CD005 | SI208 | 2.3200000 | % | NA | Figure 3 | 1999 | Jun | Jun | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 28.57500 | 28.5750 | NA | 6 | 6 | 29.45433 | 29.453 | 0.8800009 | sum | 6 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4503708 | 302.80 | 6.112869 |
| 898 | EI0976 | CD005 | SI208 | 2.6400000 | % | NA | Figure 3 | 2000 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.72050 | 29.7205 | 0.2651650 | 8 | 9 | 29.36533 | 29.813 | 0.8589678 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6821747 | 302.80 | 3.368557 |
| 899 | EI0977 | CD005 | SI208 | 0.9600000 | % | NA | Figure 3 | 2001 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.73800 | 29.7380 | 0.2192027 | 8 | 9 | 29.25034 | 29.355 | 0.7008858 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4439392 | 302.80 | 0.000000 |
| 900 | EI0978 | CD005 | SI208 | 1.2000000 | % | NA | Figure 3 | 2002 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.74800 | 29.7480 | 0.4313356 | 8 | 9 | 29.33134 | 29.608 | 0.8927529 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5910645 | 302.80 | 0.000000 |
| 901 | EI0979 | CD005 | SI208 | 5.5200000 | % | NA | Figure 3 | 2003 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.83150 | 29.8315 | 0.2708215 | 8 | 9 | 29.46200 | 29.540 | 0.6037899 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 302.80 | 0.000000 |
| 902 | EI0980 | CD005 | SI208 | 4.0000000 | % | NA | Figure 3 | 2004 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.66250 | 29.6625 | 0.7954951 | 8 | 9 | 29.74267 | 30.080 | 0.7135448 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6485596 | 302.80 | 0.000000 |
| 903 | EI0981 | CD005 | SI208 | 8.1600000 | % | NA | Figure 3 | 1998 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 30.11050 | 30.1105 | 0.7318554 | 8 | 9 | 30.05700 | 30.303 | 0.7259636 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 0.4657288 | 302.80 | 8.571403 |
| 904 | EI0982 | CD005 | SI208 | 14.0800000 | % | NA | Figure 3 | 1999 | Jun | Jun | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 28.57500 | 28.5750 | NA | 6 | 6 | 29.45433 | 29.453 | 0.8800009 | sum | 6 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 1.4503708 | 302.80 | 6.112869 |
| 905 | EI0983 | CD005 | SI208 | 4.4000000 | % | NA | Figure 3 | 2000 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.72050 | 29.7205 | 0.2651650 | 8 | 9 | 29.36533 | 29.813 | 0.8589678 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 1.6821747 | 302.80 | 3.368557 |
| 906 | EI0984 | CD005 | SI208 | 0.8000000 | % | NA | Figure 3 | 2001 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.73800 | 29.7380 | 0.2192027 | 8 | 9 | 29.25034 | 29.355 | 0.7008858 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 0.4439392 | 302.80 | 0.000000 |
| 907 | EI0985 | CD005 | SI208 | 3.1200000 | % | NA | Figure 3 | 2002 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.74800 | 29.7480 | 0.4313356 | 8 | 9 | 29.33134 | 29.608 | 0.8927529 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 1.5910645 | 302.80 | 0.000000 |
| 908 | EI0986 | CD005 | SI208 | 7.6000000 | % | NA | Figure 3 | 2003 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.83150 | 29.8315 | 0.2708215 | 8 | 9 | 29.46200 | 29.540 | 0.6037899 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 302.80 | 0.000000 |
| 909 | EI0987 | CD005 | SI208 | 1.8400000 | % | NA | Figure 3 | 2004 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.66250 | 29.6625 | 0.7954951 | 8 | 9 | 29.74267 | 30.080 | 0.7135448 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NA | 0.6485596 | 302.80 | 0.000000 |
| 910 | EI0988 | CD005 | SI208 | 2.8695652 | % | NA | Figure 3 | 1998 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 30.11050 | 30.1105 | 0.7318554 | 8 | 9 | 30.05700 | 30.303 | 0.7259636 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4657288 | 302.80 | 8.571403 |
| 911 | EI0989 | CD005 | SI208 | 5.1304348 | % | NA | Figure 3 | 1999 | Jun | Jun | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 28.57500 | 28.5750 | NA | 6 | 6 | 29.45433 | 29.453 | 0.8800009 | sum | 6 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4503708 | 302.80 | 6.112869 |
| 912 | EI0990 | CD005 | SI208 | 0.8695652 | % | NA | Figure 3 | 2000 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.72050 | 29.7205 | 0.2651650 | 8 | 9 | 29.36533 | 29.813 | 0.8589678 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6821747 | 302.80 | 3.368557 |
| 913 | EI0991 | CD005 | SI208 | 4.2608696 | % | NA | Figure 3 | 2001 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.73800 | 29.7380 | 0.2192027 | 8 | 9 | 29.25034 | 29.355 | 0.7008858 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4439392 | 302.80 | 0.000000 |
| 914 | EI0992 | CD005 | SI208 | 1.8260870 | % | NA | Figure 3 | 2002 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.74800 | 29.7480 | 0.4313356 | 8 | 9 | 29.33134 | 29.608 | 0.8927529 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5910645 | 302.80 | 0.000000 |
| 915 | EI0993 | CD005 | SI208 | 7.4782609 | % | NA | Figure 3 | 2003 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.83150 | 29.8315 | 0.2708215 | 8 | 9 | 29.46200 | 29.540 | 0.6037899 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 302.80 | 0.000000 |
| 916 | EI0994 | CD005 | SI208 | 1.1304348 | % | NA | Figure 3 | 2004 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.66250 | 29.6625 | 0.7954951 | 8 | 9 | 29.74267 | 30.080 | 0.7135448 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6485596 | 302.80 | 0.000000 |
| 917 | EI0995 | CD005 | SI208 | 3.5915490 | % | NA | Figure 3 | 1998 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 30.11050 | 30.1105 | 0.7318554 | 8 | 9 | 30.05700 | 30.303 | 0.7259636 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4657288 | 302.80 | 8.571403 |
| 918 | EI0996 | CD005 | SI208 | 4.3661970 | % | NA | Figure 3 | 1999 | Jun | Jun | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 28.57500 | 28.5750 | NA | 6 | 6 | 29.45433 | 29.453 | 0.8800009 | sum | 6 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4503708 | 302.80 | 6.112869 |
| 919 | EI0997 | CD005 | SI208 | 1.9718310 | % | NA | Figure 3 | 2000 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.72050 | 29.7205 | 0.2651650 | 8 | 9 | 29.36533 | 29.813 | 0.8589678 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6821747 | 302.80 | 3.368557 |
| 920 | EI0998 | CD005 | SI208 | 1.0563380 | % | NA | Figure 3 | 2001 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.73800 | 29.7380 | 0.2192027 | 8 | 9 | 29.25034 | 29.355 | 0.7008858 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4439392 | 302.80 | 0.000000 |
| 921 | EI0999 | CD005 | SI208 | 2.3943660 | % | NA | Figure 3 | 2002 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.74800 | 29.7480 | 0.4313356 | 8 | 9 | 29.33134 | 29.608 | 0.8927529 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5910645 | 302.80 | 0.000000 |
| 922 | EI1000 | CD005 | SI208 | 4.6478870 | % | NA | Figure 3 | 2003 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.83150 | 29.8315 | 0.2708215 | 8 | 9 | 29.46200 | 29.540 | 0.6037899 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 302.80 | 0.000000 |
| 923 | EI1001 | CD005 | SI208 | 5.0704230 | % | NA | Figure 3 | 2004 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.66250 | 29.6625 | 0.7954951 | 8 | 9 | 29.74267 | 30.080 | 0.7135448 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 1 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6485596 | 302.80 | 0.000000 |
| 924 | EI1002 | CD005 | SI208 | 1.6901410 | % | NA | Figure 3 | 1998 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 30.11050 | 30.1105 | 0.7318554 | 8 | 9 | 30.05700 | 30.303 | 0.7259636 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4657288 | 302.80 | 8.571403 |
| 925 | EI1003 | CD005 | SI208 | 1.9718310 | % | NA | Figure 3 | 1999 | Jun | Jun | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 28.57500 | 28.5750 | NA | 6 | 6 | 29.45433 | 29.453 | 0.8800009 | sum | 6 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.4503708 | 302.80 | 6.112869 |
| 926 | EI1004 | CD005 | SI208 | 1.0563380 | % | NA | Figure 3 | 2000 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.72050 | 29.7205 | 0.2651650 | 8 | 9 | 29.36533 | 29.813 | 0.8589678 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.6821747 | 302.80 | 3.368557 |
| 927 | EI1005 | CD005 | SI208 | 1.2676060 | % | NA | Figure 3 | 2001 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.73800 | 29.7380 | 0.2192027 | 8 | 9 | 29.25034 | 29.355 | 0.7008858 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.4439392 | 302.80 | 0.000000 |
| 928 | EI1006 | CD005 | SI208 | 3.9436620 | % | NA | Figure 3 | 2002 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.74800 | 29.7480 | 0.4313356 | 8 | 9 | 29.33134 | 29.608 | 0.8927529 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 1.5910645 | 302.80 | 0.000000 |
| 929 | EI1007 | CD005 | SI208 | 1.0563380 | % | NA | Figure 3 | 2003 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.83150 | 29.8315 | 0.2708215 | 8 | 9 | 29.46200 | 29.540 | 0.6037899 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.8328247 | 302.80 | 0.000000 |
| 930 | EI1008 | CD005 | SI208 | 2.3943660 | % | NA | Figure 3 | 2004 | Aug-Sep | Aug-Sep | Methods Observational data p1324 | Florida Keys and Dry Tortugas | Methods Observational data p1324 | Caribbean & Gulf of Mexico | Caribbean/Atlantic | 24.500000 | -81.50000 | 24.500000 | -81.50000 | Methods Observational data p1324, took middle of each coordinate value | NA | NA | Prevalence extracted using MetaDigitise in Rstudio n = 55 | Atlantic Ocean | 29.66250 | 29.6625 | 0.7954951 | 8 | 9 | 29.74267 | 30.080 | 0.7135448 | aut | 8 | summer | NA | NA | NA | 17.10500 | 55 | Methods Observational data p1324 | NA | 0 | NA | Circle | 55 | 9.0000 | NA | 311.0000 | Methods Observational data p1324 | length is radius and averaged (real length = 8-10) | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | NA | 0.6485596 | 302.80 | 0.000000 |
Data Exploration
Check for Erroneous Values
# Check spread of disease prevalence values and ensure all fall in % ranges
countpercent <- count(rdsdat, Disease_Prevalence)
ggplot(countpercent) +
geom_histogram(aes(x = Disease_Prevalence), color = "slateblue2", fill = "slateblue2") +
labs(x = "Disease Prevalence (%)") +
theme_bw()
Note large number of near 0% values
Disease Prevalence
# How many effect sizes report 0% disease prevalence?
count(rdsdat, Disease_Prevalence == 0)## Disease_Prevalence == 0 n
## 1 FALSE 794
## 2 TRUE 124
# How many effect sizes report disease prevalence as a %?
count(ESD, Unit_Prevalence)## # A tibble: 5 × 2
## Unit_Prevalence n
## <chr> <int>
## 1 % 932
## 2 col/100m^2 67
## 3 col/m^2 14
## 4 mean no. colonies/m^2 3
## 5 no. col 11
Sample Areas
# Check spread of survey area values
areaonly <- subset(rdsdat, Sample_Area_km2!="")
countarea <- count(areaonly, Sample_Area_km2)
ggplot(areaonly) +
geom_histogram(aes(x = Sample_Area_km2), color = "slateblue2", fill = "slateblue2")
# Scale survey area for better visualization
ggplot(areaonly) +
geom_histogram(aes(x = Sample_Area_km2), color = "slateblue2", fill = "slateblue2")+
scale_x_log10()Region Data
# Count data per region
# count(rdsdat, Region_HoeghGuldberg)
# count(rdsdat, Region_Kleypas)
# ggplot(rdsdat) +
# geom_bar(aes(x = Region_HoeghGuldberg))
ggplot(rdsdat) +
geom_bar(aes(x = Ocean, color = Ocean, fill = Ocean)) +
scale_color_viridis_d(end = 0.9) +
scale_fill_viridis_d(end = 0.9) +
theme_bw(base_size = 14) +
theme(legend.position = "bottom")Year
# Which years have the most data?
ggplot(rdsdat) +
geom_bar(aes(x = Year), color = "slateblue2", fill = "slateblue2") +
theme_bw()Survey Method
# What are the most common sampling methods?
Transect_narm <- subset(rdsdat, is.na(rdsdat$Transect_Type) != TRUE)
ggplot(Transect_narm) +
geom_bar(aes(x = Transect_Type), color = "slateblue2", fill = "slateblue2") +
labs(x = "Transect Plot Type") +
theme_bw()Map Visualizations
# Prototyping code - see Figure 1A for map
# Set map of world from existing map data
earth <- map_data("world")
# Plot map of survey locations on map
ggplot(rdsdat, aes(x = Lon, y = Lat)) +
geom_map(data = earth,
map = earth,
aes(x = long, y = lat, group = group, map_id = region),
fill = "white",
colour = "black",
size = 0.2) +
geom_point(colour = 'blue', alpha = 0.25) +
coord_quickmap()
# Plot survey locations colored by ocean
ggplot(rdsdat, aes(x = Lon, y = Lat, col = Ocean)) +
geom_map(data = earth,
map = earth,
aes(x = long, y = lat, group = group, map_id = region),
fill = "grey85",
colour = "black",
size = 0.2) +
geom_point(alpha = 0.25) +
coord_quickmap() +
labs(x = "Longitude", y = "Latitude") +
theme_bw()
# Try plotting survey locations by disease number found at each site
# Too many values for number of disease. Try merging to just one vs more than one disease per effect size
# Write function to identify the value of Disease_Num
num_dis <- function(Disease_Num) {
case_when(
Disease_Num == 1 ~ "One Disease",
Disease_Num != 1 ~ "Multiple Diseases"
)
}
# Apply function to dataset
as.DiseaseNum <- rdsdat %>% mutate(type = num_dis(Disease_Num))
# Plot survey locations on map, colored by one or multiple diseases
ggplot(as.DiseaseNum, aes(x = Lon, y = Lat, col = type)) +
geom_map(data = earth, map = earth, aes(x = long, y = lat, group = group, map_id = region), fill = "white", colour = "black", size = 0.2) +
geom_point(alpha = 0.25) +
coord_quickmap()Phylogenetic Tree
# Prototyping code - see Figure S7 for tree
genus <- unique(prevSPP$Genus[prevSPP$Genus != "Helioseris"]) # Removed the Genus Helioseris because it was removed from the analysed dataset because of the disease prevalence metric used
taxa_list <- na.omit(genus)
taxa_list2 <- as.factor(taxa_list)
taxa <- tnrs_match_names(names = levels(taxa_list2), context_name = "Animals") # Connect the list of Genera with the Open Tree taxonomy
taxa.in.tree <- ott_id(taxa)[is_in_tree(ott_id(taxa))]
tree <- tol_induced_subtree(ott_ids = taxa.in.tree, label_format = "name")
tree$tip.label <- gsub("_\\(.*","", tree$tip.label) # Remove symbols
plain_tree <- plot(tree, cex = 0.5, label.offset = 0.1, no.margin = TRUE)
is.binary(tree) # Check if binary
tree <- compute.brlen(tree, method = "Grafen", power = 1) # Compute branch lengths
all_taxa <- intersect(as.character(tree$tip.label), taxa_list) # Find synonyms and typos and remove them
used_taxa <- setdiff(as.character(tree$tip.label), taxa_list)
# Build heatmap of oceans
species <- select(prevSPP, "PaperID", "Genus")
species$Paper_ID <- species$PaperID
dat.tree <- left_join(rdsdat, species, by = c("Paper_ID")) # Join the data with the Genus information
dat.tree <- select(dat.tree, Paper_ID, Genus, Ocean) # Reduce the data to the needed columns
dat.tree <- mutate(dat.tree, search_string = decapitalize(Genus)) # Decapitalize "Genus" to match the "search string" in the "taxa" file
dat.tree <- left_join(dat.tree, select(taxa, search_string, unique_name, ott_id), by = "search_string") # Join taxa information from rotl to the dataset
dat.tree$unique_name <- word(dat.tree$unique_name, 1) # Only keep one word for the Genus (we had e.g. "Stylophora (genus in phylum Cnidaria)")
dat.tree <- dat.tree[dat.tree$unique_name %in% tree$tip.label, ] # Check that the Genera match the ones used in the tree
ocean <- dat.tree %>% group_by(unique_name) %>% summarise(
oceanIndian = Ocean == "Indian Ocean",
oceanAtlantic = Ocean == "Atlantic Ocean",
oceanPacific = Ocean == "Pacific Ocean")
ocean <- distinct(ocean) # Only keep unique rows
ocean$oceanIndian = as.numeric(ocean$oceanIndian) # convert TRUE/FALSE to binary values for each Ocean
ocean$oceanAtlantic = as.numeric(ocean$oceanAtlantic)
ocean$oceanPacific = as.numeric(ocean$oceanPacific)
ocean <- ocean %>% group_by(unique_name) %>% summarise(oceanIndian=sum(oceanIndian), # calculate the sum for each species (i.e., if 1, the species is found in the designated ocean)
oceanAtlantic=sum(oceanAtlantic),
oceanPacific=sum(oceanPacific))
ocean$oceanIndian=as.factor(ocean$oceanIndian) # Convert back to factor for the plot
ocean$oceanAtlantic=as.factor(ocean$oceanAtlantic)
ocean$oceanPacific=as.factor(ocean$oceanPacific)
# Plot Horizontal Tree
# simple phylogenetic tree
htree <- ggtree(tree, lwd = 1.05) +
geom_tiplab(offset = 0.04) # Display Genus
h <- htree %<+% ocean # Link plot to data
# plot tree and heatmap together
h2 <- h + geom_fruit(geom=geom_tile,
mapping=aes(fill=oceanAtlantic),
width=0.075,
offset=0.35) +
scale_fill_manual(name = "", values=c("white", "#7C4F85"), labels=c("", "Atlantic Ocean"), guide = guide_legend(order = 1)) +
new_scale_fill() +
geom_fruit(geom=geom_tile,
mapping=aes(fill=oceanIndian),
width=0.075,
offset=0.075)+
scale_fill_manual(name = "", values=c("white","#71A8AF"), labels=c("", "Indian Ocean"), guide = guide_legend(order = 2))+
new_scale_fill() +
geom_fruit(geom=geom_tile,
mapping=aes(fill=oceanPacific),
width=0.075,
offset=0.075)+
scale_fill_manual(name = "", values=c("white", "#D4E974"), labels=c("", "Pacific Ocean"), guide = guide_legend(order = 3))
h2Disease Number and Types
Spread of disease data
# Visualize spread of disease number data
ggplot(rdsdat) +
geom_bar(aes(x = Disease_Num), color = "slateblue2", fill = "slateblue2") +
labs(x = "Disease Number") +
theme_bw()# Plot spread of effect sizes that report one or many diseases
ggplot() +
geom_bar(rdsdat, mapping = aes(x = Disease_Num == 1), color = "slateblue2", fill = "slateblue2") +
theme_bw() +
labs(x = "Disease Number") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Multiple Diseases', 'One Disease'))# summarize data by disease
# create dataset
Disease_Counts <- data.frame(WS = count(rdsdat, WS == 1)[2,2],
BBD = count(rdsdat, BBD == 1)[2,2],
GA = count(rdsdat, GA == 1)[2,2],
BrB = count(rdsdat, BrB == 1)[2,2],
SEB = count(rdsdat, SEB == 1)[2,2],
UWS = count(rdsdat, UWS == 1)[2,2],
TL = count(rdsdat, TL == 1)[2,2],
DSS = count(rdsdat, DSS == 1)[2,2],
WB = count(rdsdat, WB == 1)[2,2],
YBD = count(rdsdat, YBD == 1)[2,2],
WPx = count(rdsdat, WPx == 1)[2,2],
IMS = count(rdsdat, IMS == 1)[2,2],
Trema = count(rdsdat, Trema == 1)[2,2],
Cyano = count(rdsdat, Cyano == 1)[2,2],
PS = count(rdsdat, PS == 1)[2,2],
AN = count(rdsdat, AN == 1)[2,2],
PR = count(rdsdat, PR == 1)[2,2],
PUWS = count(rdsdat, PUWS == 1)[2,2],
DWS = count(rdsdat, DWS == 1)[2,2],
RBD = count(rdsdat, RBD == 1)[2,2],
STGA = count(rdsdat, STGA == 1)[2,2],
RM = count(rdsdat, RM == 1)[2,2],
RW = count(rdsdat, RW == 1)[2,2],
PLS = count(rdsdat, PLS == 1)[2,2],
PWPS = count(rdsdat, PWPS == 1)[2,2],
CT = count(rdsdat, CT == 1)[2,2],
PBTL = count(rdsdat, PBTL == 1)[2,2],
WPa = count(rdsdat, WPa == 1)[2,2],
Cilia = count(rdsdat, Cilia == 1)[2,2],
PBSS = count(rdsdat, PBSS == 1)[2,2],
GPD = count(rdsdat, GPD == 1)[2,2],
Unk = count(rdsdat, Unknown == 1)[2,2])Most common diseases by ocean
#isolate data per ocean
Atlantic_Only <- subset(rdsdat, rdsdat$Ocean == "Atlantic Ocean")
Pacific_Only <- subset(rdsdat, rdsdat$Ocean == "Pacific Ocean")
Indian_Only <- subset(rdsdat, rdsdat$Ocean == "Indian Ocean")White Syndrome
WS_Atl <- ggplot() +
geom_bar(Atlantic_Only, mapping = aes(x = Atlantic_Only$WS == 1), color = "grey80", fill = "grey80") +
theme_bw() +
labs(title = "Atlantic Ocean", x = "White Syndrome") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
WS_Pac <- ggplot() +
geom_bar(Pacific_Only, mapping = aes(x = Pacific_Only$WS == 1), color = "grey80", fill = "grey80") +
theme_bw() +
labs(title = "Pacific Ocean", x = "White Syndrome") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
WS_Ind <- ggplot() +
geom_bar(Indian_Only, mapping = aes(x = Indian_Only$WS == 1), color = "grey80", fill = "grey80") +
theme_bw() +
labs(title = "Indian Ocean", x = "White Syndrome") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
WS_Atl + WS_Pac + WS_IndBlack Band Disease
BBD_Atl <- ggplot() +
geom_bar(Atlantic_Only, mapping = aes(x = Atlantic_Only$BBD == 1), color = "black", fill = "black") +
theme_bw() +
labs(title = "Atlantic Ocean", x = "Black Band Disease") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
BBD_Pac <- ggplot() +
geom_bar(Pacific_Only, mapping = aes(x = Pacific_Only$BBD == 1), color = "black", fill = "black") +
theme_bw() +
labs(title = "Pacific Ocean", x = "Black Band Disease") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
BBD_Ind <- ggplot() +
geom_bar(Indian_Only, mapping = aes(x = Indian_Only$BBD == 1), color = "black", fill = "black") +
theme_bw() +
labs(title = "Indian Ocean", x = "Black Band Disease") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
BBD_Atl + BBD_Pac + BBD_IndYellow Band Disease
YBD_Atl <- ggplot() +
geom_bar(Atlantic_Only, mapping = aes(x = Atlantic_Only$YBD == 1), color = "yellow", fill = "yellow") +
theme_bw() +
labs(title = "Atlantic Ocean", x = "Yellow Band Disease") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
YBD_Pac <- ggplot() +
geom_bar(Pacific_Only, mapping = aes(x = Pacific_Only$YBD == 1), color = "yellow", fill = "yellow") +
theme_bw() +
labs(title = "Pacific Ocean", x = "Yellow Band Disease") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
YBD_Ind <- ggplot() +
geom_bar(Indian_Only, mapping = aes(x = Indian_Only$YBD == 1), color = "yellow", fill = "yellow") +
theme_bw() +
labs(title = "Indian Ocean", x = "Yellow Band Disease") +
theme(text = element_text(size = 14)) +
scale_x_discrete(labels = c('Absent', 'Present'))
YBD_Atl + YBD_Pac + YBD_Ind
### {-}
Hemisphere data
North Hemisphere
# prototyping code
# Isolate North hemisphere values
poslat <- subset(rdsdat, Lat > "0") # Need to split into proper month format rather than the written format
# Table of North hemisphere values
table(poslat$start_month) -> Ncounts
# change table to dataframe
Ncounts <- as.data.frame(t(Ncounts))
# rename values to actual month name for axis values
Ncounts$Var2 <- c('Jan', "Feb", 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec')
# rename column for axis label
names(Ncounts)[2] <- 'Month'
# plot count of survey by start month in north
Nhemi <- ggplot(Ncounts) +
geom_bar(aes(x=Month, y=Freq), color = "darkorchid3", fill = "darkorchid3", stat = 'identity') +
theme_bw() +
scale_x_discrete(limits = c('Jan', "Feb", 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec')) +
labs(y = "North Freq") +
theme(text = element_text(size = 15))
NhemiSouth Hemisphere
# prototyping code
# Isolate South hemisphere values
neglat <- subset(rdsdat, Lat < "0")
# Table of South hemisphere values
Scounts <- table(neglat$start_month)
# Change table to dataframe
Scounts <- as.data.frame(t(Scounts))
# Rename values to actual month name for axis values
Scounts$Var2 <- c('Jan', "Feb", 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec')
# Rename column for axis label
names(Scounts)[2] <- 'Month'
# plot count of survey by start month in south
Shemi <- ggplot(Scounts) +
geom_bar(aes(x=Month, y=Freq), color = "gold2", fill = "gold2", stat = 'identity') +
theme(text = element_text(size = 50)) +
theme_bw() +
scale_y_reverse() +
scale_x_discrete(limits = c('Jan', "Feb", 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'), position = "top") +
labs(y = "South Freq")
ShemiMirror Hemispheres
# prototyping code
# Mirror view of Hemispheres
Nhemi/ShemiMeta-Analytic Models
Scale and Center Data
# Change percentage to a proportion
rdsdat$Disease_P <- (rdsdat$Disease_Prevalence)/100
# Scale predictors
rdsdat$sYear <- scale(rdsdat$Year)
rdsdat$sSumTemp <- scale(rdsdat$average_SST_summer)
rdsdat$sWSSTA <- scale(rdsdat$WSSTA)
rdsdat$sDisease_Num <- scale(rdsdat$Disease_Num)
rdsdat$logArea <- log(rdsdat$Sample_Area_km2*10e5)
# Center predictors
rdsdat$cYear <- scale(rdsdat$Year, scale = F)
rdsdat$cSumTemp <- scale(rdsdat$average_SST_summer, scale = F)Run Models
These models take very long to run and are too big to send through to GitHub. We have provided these models for download here.
Model with no interaction between key variables (WSSTA, SST, and Year)
no_interaction_f <- brmsformula(
Disease_P|weights(logArea) ~ # estimates weighed by the logarithm of the sample area
sYear + # Scaled sample year
sSumTemp + # Scaled summer temperature
sWSSTA + # Scaled weekly sea surface temperature anomaly
sDisease_Num + # Scaled number of diseases
Ocean + # Ocean basin
(1| Site_ID) + # Site as a random factor
(1|Paper_ID) + # Study as a random factor
(1|season) + # Season as a random factor
(1|Transect_Type), # Type of transect as a random factor
zi ~ 1 + sSumTemp + sWSSTA + sYear, # zi = zero-inflation
phi ~ 1 + sSumTemp + sWSSTA + sYear) # phi = heteroscedasticity
no_interaction <- brm(no_interaction_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))no_interaction <- readRDS(here("Rdata","no_interaction_mod.rds"))
summary(no_interaction)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear + sSumTemp + sWSSTA + sDisease_Num + Ocean + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.30 0.12 1.07 1.55 1.00 1721 2254
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.88 0.48 0.36 2.20 1.00 3434 3070
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.62 0.06 0.52 0.75 1.00 1138 2106
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.76 0.47 0.24 1.97 1.00 2807 2743
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept -2.36 0.65 -3.60 -1.01 1.00 2217 2537
## phi_Intercept 2.89 0.02 2.86 2.93 1.00 9975 2544
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 11210 2743
## sYear 0.25 0.03 0.19 0.31 1.00 10128 2786
## sSumTemp 0.28 0.04 0.21 0.35 1.00 8854 2963
## sWSSTA 0.20 0.02 0.16 0.23 1.00 9039 3053
## sDisease_Num 0.38 0.11 0.16 0.60 1.00 2426 2862
## OceanIndianOcean -0.42 0.38 -1.15 0.33 1.00 1927 2743
## OceanPacificOcean -0.31 0.31 -0.94 0.28 1.00 1732 2535
## phi_sSumTemp -0.25 0.01 -0.27 -0.22 1.00 10035 2743
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 9424 3468
## phi_sYear 0.31 0.02 0.28 0.34 1.00 8156 2969
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 12415 2494
## zi_sWSSTA -0.17 0.03 -0.24 -0.11 1.00 9507 2642
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 13090 3053
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interactions between all key variables and Ocean
all_interaction_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear*Ocean +
sSumTemp*Ocean +
sWSSTA*Ocean +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
all_interaction <- brm(all_interaction_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))all_interaction <- readRDS(here("Rdata","all_interaction_mod.rds"))
summary(all_interaction)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear * Ocean + sSumTemp * Ocean + sWSSTA * Ocean + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.31 0.12 1.09 1.57 1.00 1983 2646
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.89 0.49 0.37 2.22 1.00 2999 2718
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.61 0.06 0.51 0.73 1.00 1347 2390
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.75 0.44 0.23 1.96 1.00 3142 2871
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.35 0.64 -3.59 -0.98 1.00 2135
## phi_Intercept 2.90 0.02 2.87 2.93 1.00 6038
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 7062
## sYear 0.24 0.03 0.17 0.31 1.00 6835
## OceanIndianOcean -0.11 0.44 -0.97 0.76 1.00 2049
## OceanPacificOcean -0.54 0.34 -1.20 0.11 1.00 2212
## sSumTemp 0.31 0.04 0.23 0.39 1.00 6061
## sWSSTA 0.20 0.02 0.16 0.24 1.00 6329
## sDisease_Num 0.38 0.11 0.16 0.61 1.00 2919
## sYear:OceanIndianOcean -0.34 0.26 -0.83 0.17 1.00 5001
## sYear:OceanPacificOcean 0.24 0.13 -0.01 0.50 1.00 5838
## OceanIndianOcean:sSumTemp 0.07 0.11 -0.16 0.29 1.00 4575
## OceanPacificOcean:sSumTemp -0.24 0.10 -0.43 -0.05 1.00 5369
## OceanIndianOcean:sWSSTA -0.02 0.05 -0.12 0.08 1.00 4604
## OceanPacificOcean:sWSSTA -0.02 0.08 -0.18 0.15 1.00 4363
## phi_sSumTemp -0.25 0.01 -0.28 -0.22 1.00 6492
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 6074
## phi_sYear 0.31 0.02 0.28 0.34 1.00 6420
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 5933
## zi_sWSSTA -0.17 0.03 -0.24 -0.11 1.00 6136
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 7073
## Tail_ESS
## Intercept 2254
## phi_Intercept 2649
## zi_Intercept 2815
## sYear 2711
## OceanIndianOcean 2635
## OceanPacificOcean 2428
## sSumTemp 3471
## sWSSTA 3466
## sDisease_Num 2730
## sYear:OceanIndianOcean 2856
## sYear:OceanPacificOcean 2889
## OceanIndianOcean:sSumTemp 2778
## OceanPacificOcean:sSumTemp 2760
## OceanIndianOcean:sWSSTA 3231
## OceanPacificOcean:sWSSTA 2569
## phi_sSumTemp 2967
## phi_sWSSTA 3273
## phi_sYear 3448
## zi_sSumTemp 2628
## zi_sWSSTA 2911
## zi_sYear 3147
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interaction between Year and Ocean and SST and Ocean only
YearxOcean_SSTxOcean_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear*Ocean +
sSumTemp*Ocean +
sWSSTA +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
YearxOcean_SSTxOcean <- brm(YearxOcean_SSTxOcean_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))YearxOcean_SSTxOcean <- readRDS(here("Rdata","YearxOcean_SSTxOcean_mod.rds"))
summary(YearxOcean_SSTxOcean)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear * Ocean + sSumTemp * Ocean + sWSSTA + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.32 0.12 1.09 1.57 1.00 1689 2325
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.89 0.47 0.37 2.13 1.00 3916 2852
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.61 0.06 0.51 0.73 1.00 1422 2433
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.76 0.47 0.23 2.01 1.00 3784 2886
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.35 0.61 -3.52 -1.06 1.00 2695
## phi_Intercept 2.90 0.02 2.87 2.93 1.00 7936
## zi_Intercept -1.89 0.03 -1.95 -1.84 1.00 10078
## sYear 0.24 0.03 0.17 0.30 1.00 7908
## OceanIndianOcean -0.09 0.43 -0.92 0.76 1.00 2490
## OceanPacificOcean -0.53 0.33 -1.19 0.10 1.00 2053
## sSumTemp 0.31 0.04 0.23 0.38 1.00 7310
## sWSSTA 0.20 0.02 0.16 0.23 1.00 8137
## sDisease_Num 0.38 0.11 0.17 0.60 1.00 2877
## sYear:OceanIndianOcean -0.38 0.23 -0.81 0.07 1.00 7243
## sYear:OceanPacificOcean 0.24 0.12 0.01 0.48 1.00 6466
## OceanIndianOcean:sSumTemp 0.06 0.11 -0.16 0.28 1.00 7837
## OceanPacificOcean:sSumTemp -0.24 0.10 -0.43 -0.05 1.00 5905
## phi_sSumTemp -0.25 0.01 -0.28 -0.22 1.00 8819
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 7725
## phi_sYear 0.31 0.02 0.28 0.34 1.00 7588
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 11260
## zi_sWSSTA -0.17 0.03 -0.24 -0.11 1.00 9420
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 10302
## Tail_ESS
## Intercept 2740
## phi_Intercept 2553
## zi_Intercept 2645
## sYear 3497
## OceanIndianOcean 3032
## OceanPacificOcean 2543
## sSumTemp 3403
## sWSSTA 3086
## sDisease_Num 2754
## sYear:OceanIndianOcean 3051
## sYear:OceanPacificOcean 3150
## OceanIndianOcean:sSumTemp 2916
## OceanPacificOcean:sSumTemp 2914
## phi_sSumTemp 3127
## phi_sWSSTA 3265
## phi_sYear 3411
## zi_sSumTemp 2438
## zi_sWSSTA 2591
## zi_sYear 2902
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interaction between SST and Ocean and WSSTA and Ocean only
SSTxOcean_WSSTAxOcean_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear +
sSumTemp*Ocean +
sWSSTA*Ocean +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
SSTxOcean_WSSTAxOcean <- brm(SSTxOcean_WSSTAxOcean_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))SSTxOcean_WSSTAxOcean <- readRDS(here("Rdata","SSTxOcean_WSSTAxOcean_mod.rds"))
summary(SSTxOcean_WSSTAxOcean)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear + sSumTemp * Ocean + sWSSTA * Ocean + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.30 0.12 1.08 1.56 1.00 2110 2863
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.88 0.46 0.37 2.05 1.00 4022 2772
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.62 0.06 0.52 0.74 1.00 1338 2344
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.72 0.43 0.23 1.89 1.00 3409 2928
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.37 0.62 -3.54 -1.04 1.00 3433
## phi_Intercept 2.89 0.02 2.86 2.92 1.00 5428
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 5982
## sYear 0.25 0.03 0.18 0.32 1.00 6784
## sSumTemp 0.31 0.04 0.23 0.38 1.00 5413
## OceanIndianOcean -0.45 0.39 -1.20 0.30 1.00 2893
## OceanPacificOcean -0.41 0.32 -1.05 0.22 1.00 2794
## sWSSTA 0.20 0.02 0.16 0.24 1.00 5710
## sDisease_Num 0.38 0.11 0.16 0.60 1.00 4439
## sSumTemp:OceanIndianOcean 0.08 0.12 -0.15 0.32 1.00 6799
## sSumTemp:OceanPacificOcean -0.23 0.09 -0.42 -0.04 1.00 6849
## OceanIndianOcean:sWSSTA -0.05 0.05 -0.14 0.04 1.00 5723
## OceanPacificOcean:sWSSTA 0.02 0.08 -0.14 0.18 1.00 5666
## phi_sSumTemp -0.25 0.01 -0.27 -0.22 1.00 5866
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 5898
## phi_sYear 0.31 0.02 0.28 0.34 1.00 5752
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 5757
## zi_sWSSTA -0.17 0.03 -0.24 -0.10 1.00 5287
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 5527
## Tail_ESS
## Intercept 2568
## phi_Intercept 2646
## zi_Intercept 2717
## sYear 3128
## sSumTemp 3528
## OceanIndianOcean 2915
## OceanPacificOcean 2600
## sWSSTA 3009
## sDisease_Num 2706
## sSumTemp:OceanIndianOcean 2718
## sSumTemp:OceanPacificOcean 2959
## OceanIndianOcean:sWSSTA 3247
## OceanPacificOcean:sWSSTA 2696
## phi_sSumTemp 2928
## phi_sWSSTA 2964
## phi_sYear 3251
## zi_sSumTemp 2841
## zi_sWSSTA 3015
## zi_sYear 2630
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interaction between Year and Ocean and WSSTA and Ocean only
YearxOcean_WSSTAxOcean_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear*Ocean +
sSumTemp +
sWSSTA*Ocean +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
YearxOcean_WSSTAxOcean <- brm(YearxOcean_WSSTAxOcean_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))YearxOcean_WSSTAxOcean <- readRDS(here("Rdata","YearxOcean_WSSTAxOcean_mod.rds"))
summary(YearxOcean_WSSTAxOcean)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear * Ocean + sSumTemp + sWSSTA * Ocean + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.32 0.13 1.09 1.60 1.00 2053 2600
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.87 0.47 0.36 2.14 1.00 3430 2714
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.63 0.06 0.53 0.75 1.00 1489 2369
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.76 0.44 0.25 1.95 1.00 2854 2929
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.37 0.63 -3.56 -1.04 1.00 2817
## phi_Intercept 2.90 0.02 2.87 2.93 1.00 5906
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 7012
## sYear 0.24 0.03 0.18 0.31 1.00 6344
## OceanIndianOcean -0.10 0.45 -1.02 0.76 1.00 2928
## OceanPacificOcean -0.46 0.33 -1.12 0.20 1.00 2529
## sSumTemp 0.28 0.03 0.21 0.35 1.00 6097
## sWSSTA 0.20 0.02 0.16 0.25 1.00 6970
## sDisease_Num 0.39 0.11 0.18 0.62 1.00 3543
## sYear:OceanIndianOcean -0.36 0.26 -0.86 0.14 1.00 5552
## sYear:OceanPacificOcean 0.23 0.13 -0.02 0.48 1.00 5473
## OceanIndianOcean:sWSSTA -0.01 0.05 -0.11 0.09 1.00 5291
## OceanPacificOcean:sWSSTA -0.02 0.09 -0.20 0.15 1.00 5098
## phi_sSumTemp -0.25 0.01 -0.28 -0.22 1.00 6224
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 6414
## phi_sYear 0.31 0.02 0.28 0.34 1.00 6254
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 6401
## zi_sWSSTA -0.17 0.03 -0.24 -0.11 1.00 6099
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 5735
## Tail_ESS
## Intercept 2571
## phi_Intercept 2761
## zi_Intercept 2897
## sYear 3034
## OceanIndianOcean 2208
## OceanPacificOcean 2402
## sSumTemp 2815
## sWSSTA 3548
## sDisease_Num 2779
## sYear:OceanIndianOcean 2597
## sYear:OceanPacificOcean 2931
## OceanIndianOcean:sWSSTA 3149
## OceanPacificOcean:sWSSTA 3023
## phi_sSumTemp 3025
## phi_sWSSTA 3242
## phi_sYear 2639
## zi_sSumTemp 2727
## zi_sWSSTA 2570
## zi_sYear 2625
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interaction between Year and Ocean only
YearxOcean_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear*Ocean +
sSumTemp +
sWSSTA +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
YearxOcean <- brm(YearxOcean_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))YearxOcean <- readRDS(here("Rdata","YearxOcean_mod.rds"))
summary(YearxOcean)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear * Ocean + sSumTemp + sWSSTA + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.32 0.13 1.09 1.59 1.00 2081 2934
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.87 0.46 0.37 2.04 1.00 4605 3179
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.62 0.06 0.52 0.75 1.00 1505 2625
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.76 0.44 0.25 1.89 1.00 3428 3257
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.38 0.63 -3.62 -1.06 1.00 3721
## phi_Intercept 2.90 0.02 2.87 2.93 1.00 5443
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 6448
## sYear 0.24 0.03 0.18 0.31 1.00 6726
## OceanIndianOcean -0.08 0.43 -0.91 0.77 1.00 3616
## OceanPacificOcean -0.45 0.33 -1.08 0.20 1.00 3027
## sSumTemp 0.28 0.03 0.21 0.35 1.00 7135
## sWSSTA 0.20 0.02 0.17 0.24 1.00 6629
## sDisease_Num 0.38 0.12 0.16 0.62 1.00 3923
## sYear:OceanIndianOcean -0.38 0.23 -0.83 0.06 1.00 8478
## sYear:OceanPacificOcean 0.22 0.12 -0.01 0.47 1.00 7331
## phi_sSumTemp -0.25 0.01 -0.28 -0.22 1.00 7273
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 6788
## phi_sYear 0.31 0.02 0.28 0.34 1.00 6340
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 6693
## zi_sWSSTA -0.17 0.03 -0.24 -0.11 1.00 5946
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 6088
## Tail_ESS
## Intercept 2763
## phi_Intercept 2853
## zi_Intercept 2763
## sYear 3095
## OceanIndianOcean 3121
## OceanPacificOcean 2562
## sSumTemp 2996
## sWSSTA 3555
## sDisease_Num 2916
## sYear:OceanIndianOcean 2933
## sYear:OceanPacificOcean 3060
## phi_sSumTemp 3172
## phi_sWSSTA 2947
## phi_sYear 3130
## zi_sSumTemp 2998
## zi_sWSSTA 2795
## zi_sYear 2489
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interaction between WSSTA and Ocean only
WSSTAxOcean_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear +
sSumTemp +
sWSSTA*Ocean +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
WSSTAxOcean <- brm(WSSTAxOcean_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))WSSTAxOcean <- readRDS(here("Rdata","WSSTAxOcean_mod.rds"))
summary(WSSTAxOcean)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear + sSumTemp + sWSSTA * Ocean + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.30 0.12 1.08 1.55 1.00 1567 2260
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.87 0.46 0.36 2.13 1.00 2697 2654
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.63 0.06 0.53 0.75 1.00 1286 1954
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.74 0.43 0.24 1.88 1.00 2422 2378
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.38 0.58 -3.51 -1.17 1.00 2099
## phi_Intercept 2.89 0.02 2.86 2.93 1.00 6891
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 7268
## sYear 0.25 0.03 0.19 0.32 1.00 6553
## sSumTemp 0.28 0.03 0.21 0.34 1.00 6139
## sWSSTA 0.21 0.02 0.17 0.24 1.00 5929
## OceanIndianOcean -0.45 0.38 -1.19 0.30 1.00 1371
## OceanPacificOcean -0.33 0.32 -0.92 0.29 1.00 1519
## sDisease_Num 0.37 0.11 0.16 0.60 1.00 2152
## sWSSTA:OceanIndianOcean -0.05 0.04 -0.13 0.04 1.00 6267
## sWSSTA:OceanPacificOcean 0.02 0.08 -0.14 0.18 1.00 3816
## phi_sSumTemp -0.25 0.01 -0.27 -0.22 1.00 7532
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 6285
## phi_sYear 0.31 0.02 0.28 0.34 1.00 6616
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 7135
## zi_sWSSTA -0.17 0.03 -0.24 -0.10 1.00 6327
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 6851
## Tail_ESS
## Intercept 2491
## phi_Intercept 2809
## zi_Intercept 2814
## sYear 3029
## sSumTemp 2867
## sWSSTA 3489
## OceanIndianOcean 1926
## OceanPacificOcean 2257
## sDisease_Num 2538
## sWSSTA:OceanIndianOcean 3213
## sWSSTA:OceanPacificOcean 2696
## phi_sSumTemp 2533
## phi_sWSSTA 3174
## phi_sYear 2810
## zi_sSumTemp 2712
## zi_sWSSTA 2354
## zi_sYear 2714
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model with interaction between SST and Ocean only
SSTxOcean_f <- brmsformula(
Disease_P|weights(logArea) ~
sYear +
sSumTemp*Ocean +
sWSSTA +
sDisease_Num +
(1|Site_ID) +
(1|Paper_ID) +
(1|season) +
(1|Transect_Type),
zi ~ 1 + sSumTemp + sWSSTA + sYear,
phi ~ 1 + sSumTemp + sWSSTA + sYear)
SSTxOcean <- brm(SSTxOcean_f,
chains = 2,
iter = 30000,
warmup = 28000,
data = rdsdat,
family = zero_inflated_beta(link = "logit", link_phi = "log", link_zi = "logit"),
control = list(adapt_delta = 0.95))SSTxOcean <- readRDS(here("Rdata","SSTxOcean_mod.rds"))
summary(SSTxOcean)## Family: zero_inflated_beta
## Links: mu = logit; phi = log; zi = logit
## Formula: Disease_P | weights(logArea) ~ sYear + sSumTemp * Ocean + sWSSTA + sDisease_Num + (1 | Site_ID) + (1 | Paper_ID) + (1 | season) + (1 | Transect_Type)
## zi ~ 1 + sSumTemp + sWSSTA + sYear
## phi ~ 1 + sSumTemp + sWSSTA + sYear
## Data: rdsdat (Number of observations: 918)
## Draws: 2 chains, each with iter = 30000; warmup = 28000; thin = 1;
## total post-warmup draws = 4000
##
## Group-Level Effects:
## ~Paper_ID (Number of levels: 108)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 1.29 0.12 1.07 1.55 1.00 2301 3012
##
## ~season (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.89 0.46 0.38 2.12 1.00 3490 3017
##
## ~Site_ID (Number of levels: 199)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.61 0.06 0.51 0.73 1.00 1449 2696
##
## ~Transect_Type (Number of levels: 5)
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept) 0.73 0.43 0.24 1.92 1.00 2839 2610
##
## Population-Level Effects:
## Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS
## Intercept -2.35 0.61 -3.49 -0.97 1.00 3401
## phi_Intercept 2.89 0.02 2.86 2.92 1.00 5308
## zi_Intercept -1.90 0.03 -1.95 -1.84 1.00 5870
## sYear 0.25 0.03 0.18 0.31 1.00 7706
## sSumTemp 0.31 0.04 0.24 0.39 1.00 7382
## OceanIndianOcean -0.43 0.38 -1.18 0.30 1.00 3088
## OceanPacificOcean -0.39 0.31 -1.01 0.21 1.00 2894
## sWSSTA 0.19 0.02 0.16 0.23 1.00 7822
## sDisease_Num 0.37 0.11 0.15 0.60 1.00 3616
## sSumTemp:OceanIndianOcean 0.04 0.11 -0.17 0.26 1.00 9325
## sSumTemp:OceanPacificOcean -0.23 0.10 -0.42 -0.05 1.00 7484
## phi_sSumTemp -0.25 0.01 -0.27 -0.22 1.00 5706
## phi_sWSSTA -0.24 0.01 -0.26 -0.22 1.00 6155
## phi_sYear 0.31 0.02 0.28 0.34 1.00 6297
## zi_sSumTemp 0.13 0.03 0.08 0.19 1.00 6273
## zi_sWSSTA -0.17 0.03 -0.24 -0.11 1.00 6072
## zi_sYear -0.03 0.03 -0.08 0.02 1.00 6194
## Tail_ESS
## Intercept 3100
## phi_Intercept 2398
## zi_Intercept 2608
## sYear 3369
## sSumTemp 3162
## OceanIndianOcean 2961
## OceanPacificOcean 2991
## sWSSTA 3141
## sDisease_Num 2997
## sSumTemp:OceanIndianOcean 3373
## sSumTemp:OceanPacificOcean 2957
## phi_sSumTemp 2921
## phi_sWSSTA 2854
## phi_sYear 3504
## zi_sSumTemp 2923
## zi_sWSSTA 3075
## zi_sYear 2680
##
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).
Model Comparisons
Leave-One-Out Comparisons
# Fit Models for LOO Comparison
fit_no_interaction <- add_criterion(no_interaction, "loo")
fit_all_interaction <- add_criterion(all_interaction, "loo")
fit_YearxOcean_SSTxOcean <- add_criterion(YearxOcean_SSTxOcean, "loo")
fit_SSTxOcean_WSSTAxOcean <- add_criterion(SSTxOcean_WSSTAxOcean, "loo")
fit_YearxOcean_WSSTAxOcean <- add_criterion(YearxOcean_WSSTAxOcean, "loo")
fit_YearxOcean <- add_criterion(YearxOcean, "loo")
fit_WSSTAxOcean <- add_criterion(WSSTAxOcean, "loo")
fit_SSTxOcean <- add_criterion(SSTxOcean, "loo")
# LOO Comparison
lootest <- loo_compare(fit_SSTxOcean,
fit_all_interaction,
fit_no_interaction,
fit_YearxOcean_SSTxOcean,
fit_SSTxOcean_WSSTAxOcean,
fit_YearxOcean_WSSTAxOcean,
fit_YearxOcean,
fit_WSSTAxOcean,
criterion = "loo",
model_names = NULL)
print(lootest, simplify = F)## elpd_diff se_diff elpd_loo se_elpd_loo p_loo
## fit_no_interaction 0.0 0.0 17702.5 1243.9 1302.2
## fit_WSSTAxOcean -6.1 9.2 17696.4 1243.9 1314.9
## fit_YearxOcean -10.0 12.9 17692.5 1244.6 1326.0
## fit_SSTxOcean_WSSTAxOcean -14.9 12.0 17687.7 1245.4 1326.3
## fit_YearxOcean_SSTxOcean -17.9 17.9 17684.6 1244.8 1330.9
## fit_SSTxOcean -21.5 10.9 17681.0 1246.0 1340.4
## fit_all_interaction -25.9 16.3 17676.7 1245.4 1349.9
## fit_YearxOcean_WSSTAxOcean -29.6 14.5 17673.0 1246.0 1355.5
## se_p_loo looic se_looic
## fit_no_interaction 99.7 -35405.0 2487.9
## fit_WSSTAxOcean 100.2 -35392.8 2487.9
## fit_YearxOcean 102.5 -35385.0 2489.3
## fit_SSTxOcean_WSSTAxOcean 100.5 -35375.3 2490.8
## fit_YearxOcean_SSTxOcean 100.9 -35369.2 2489.5
## fit_SSTxOcean 103.9 -35362.0 2491.9
## fit_all_interaction 101.5 -35353.3 2490.8
## fit_YearxOcean_WSSTAxOcean 105.6 -35345.9 2492.0
WAIC Comparisons
# WAIC Comparison
waic(no_interaction)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17666.3 1250.4
## p_waic 1338.4 119.4
## waic -35332.7 2500.8
##
## 443 (48.3%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(all_interaction)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17637.9 1251.7
## p_waic 1388.7 121.4
## waic -35275.7 2503.3
##
## 442 (48.1%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(YearxOcean_SSTxOcean)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17652.2 1251.3
## p_waic 1363.3 119.5
## waic -35304.4 2502.5
##
## 436 (47.5%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(SSTxOcean_WSSTAxOcean)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17649.5 1251.5
## p_waic 1364.5 119.7
## waic -35299.0 2503.0
##
## 445 (48.5%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(YearxOcean_WSSTAxOcean)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17651.4 1251.5
## p_waic 1377.1 121.6
## waic -35302.8 2502.9
##
## 455 (49.6%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(YearxOcean)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17666.7 1250.8
## p_waic 1351.9 119.0
## waic -35333.3 2501.5
##
## 444 (48.4%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(WSSTAxOcean)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17663.5 1249.9
## p_waic 1347.8 118.4
## waic -35326.9 2499.9
##
## 439 (47.8%) p_waic estimates greater than 0.4. We recommend trying loo instead.
waic(SSTxOcean)##
## Computed from 4000 by 918 log-likelihood matrix
##
## Estimate SE
## elpd_waic 17669.2 1249.9
## p_waic 1352.2 119.3
## waic -35338.4 2499.8
##
## 446 (48.6%) p_waic estimates greater than 0.4. We recommend trying loo instead.
# p_waic estimates greater than 0.4, use LOO instead for comparisonWe find the no_interaction and YearxOcean_SSTxOcean interaction models to be the best fits
Unscale Data
We need means and standard deviation for WSSTA, SumTemp, and Year to convert out of scale
meanSD <- rdsdat %>% summarise(Year_mean = mean(Year,na.rm = T),
Year_SD = sd(Year,na.rm = T),
WSSTA_mean = mean(WSSTA,na.rm = T),
WSSTA_SD = sd(WSSTA,na.rm = T),
SumTemp_mean = mean(average_SST_summer,na.rm = T),
SumTemp_SD = sd(average_SST_summer,na.rm = T)
)
meanSD## Year_mean Year_SD WSSTA_mean WSSTA_SD SumTemp_mean SumTemp_SD
## 1 2006.41 5.322735 2.082593 3.757537 28.64199 1.02596
Future Predictions of Disease Prevalence
2018
# last year of data
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2018-meanSD$Year_mean)/meanSD$Year_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 2.18 0.0992 0.0208 0.245
##
## Point estimate displayed: median
## HPD interval probability: 0.95
2022
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2022-meanSD$Year_mean)/meanSD$Year_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 2.93 0.117 0.0267 0.282
##
## Point estimate displayed: median
## HPD interval probability: 0.95
2050
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2050-meanSD$Year_mean)/meanSD$Year_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 8.19 0.319 0.102 0.598
##
## Point estimate displayed: median
## HPD interval probability: 0.95
2100
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2100-meanSD$Year_mean)/meanSD$Year_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 17.6 0.768 0.532 0.929
##
## Point estimate displayed: median
## HPD interval probability: 0.95
2100 with RCP 8.5
# 2015 IPCC RCP 8.5 "business as usual" predictions
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2100-meanSD$Year_mean)/meanSD$Year_SD, sSumTemp = (32-meanSD$SumTemp_mean)/meanSD$SumTemp_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 17.6 0.805 0.644 0.924
##
## Point estimate displayed: median
## HPD interval probability: 0.95
Average summer SST alone increasing to RCP 8.5 levels
# effect of if the Year didn't accelerate past last data point, and only average summer temperature changed
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2018-meanSD$Year_mean)/meanSD$Year_SD, sSumTemp = (32-meanSD$SumTemp_mean)/meanSD$SumTemp_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 2.18 0.196 0.0547 0.411
##
## Point estimate displayed: median
## HPD interval probability: 0.95
WSSTA Doubles
# Effect of WSSTA independent of year and summer temperature
# assume arbitrarily that anomalies will get 2x more intense in future
# keeping year at 2018 so we don't account for any predicted changes in temperature that would occur when we predict the future years
no_interaction %>%
emmeans(~ sYear,
at = list(sYear = (2018-meanSD$Year_mean)/meanSD$Year_SD, sWSSTA = ((meanSD$WSSTA_mean*2)-meanSD$WSSTA_mean)/meanSD$WSSTA_SD),
epred = TRUE,
re_formula = NA)## sYear emmean lower.HPD upper.HPD
## 2.18 0.111 0.0231 0.267
##
## Point estimate displayed: median
## HPD interval probability: 0.95
Figures
Figure 1
Location data characteristics
Figure 1A
earth <- map_data("world") # World map
# Map of survey locations, colored by Ocean basin
OceanMap <- ggplot() +
geom_map(data = earth,
map = earth,
aes(x = long, y = lat, group = group, map_id = region),
fill = "grey95",
colour = "grey65",
size = 0.2) +
scale_fill_viridis_d(end = 0.9) +
scale_colour_manual(breaks = c("TRUE", "FALSE"), values = c("darkorchid3", "gold2")) +
scale_x_continuous(breaks = c(-180,-120,-60,0,60,120,180)) +
scale_y_continuous(breaks = c(-66,-23,0,23,66), limits = c(-77,77)) +
geom_point(data = rdsdat, aes(x = Lon, y = Lat, fill = Ocean,
colour = as.factor(rdsdat$Lat > 0)),
alpha = 0.4, colour = "grey50",
size = 4, shape = 21) +
guides(fill = "legend") +
#coord_quickmap() +
labs(x = "Longitude", y = "Latitude") +
theme_bw(base_size = 20) +
theme(panel.grid.minor = element_blank()) +
theme (legend.position = "none")
# Histogram of surveys by latitude
OceanMapM <- ggMarginal(OceanMap, type = "hist", margins = "y", size = 10,
bins = 31, fill = "grey40",
colour = "white")Figure 1B
# Subset Northern Hemisphere data
poslat <- subset(rdsdat, Lat > "0")
# Table for Northern Hemisphere values
table(poslat$start_month) -> Ncounts
# Change table to dataframe
Ncounts <- as.data.frame(t(Ncounts))
# Rename values to actual month name for axis values
Ncounts$Var2 <- c('Jan',
"Feb",
'Mar',
'Apr',
'May',
'Jun',
'Jul',
'Aug',
'Sep',
'Oct',
'Nov',
'Dec')
# Rename column for axis label
names(Ncounts)[2] <- 'Month'
# Subset Southern Hemisphere data
neglat <- subset(rdsdat, Lat < "0")
# Table for Southern Hemisphere values
Scounts <- table(neglat$start_month)
# Change table to dataframe
Scounts <- as.data.frame(t(Scounts))
# Rename values to actual month name for axis values
Scounts$Var2 <- c('Jan',
"Feb",
'Mar',
'Apr',
'May',
'Jun',
'Jul',
'Aug',
'Sep',
'Oct',
'Nov',
'Dec')
# Rename column for axis label
names(Scounts)[2] <- 'Month'
# Plot number of estimates for each month per Hemisphere
Hemi <- ggplot(Scounts) +
geom_bar(aes(x=Month, y=-1*Freq),
color = "gold2",
fill = "gold2",
stat = 'identity') +
theme_bw(base_size = 20) +
theme(panel.grid.minor = element_blank()) +
geom_bar(data = Ncounts, aes(x=Month, y=Freq),
stat = 'identity',
color = "darkorchid3",
fill = "darkorchid3") +
scale_y_continuous(breaks = c(-50,0,50,100,150,200),
labels = c(50,0,50,100,150,200)) +
scale_x_discrete(limits = c('Jan',
"Feb",
'Mar',
'Apr',
'May',
'Jun',
'Jul',
'Aug',
'Sep',
'Oct',
'Nov',
'Dec'),
labels = c('J','F','M','A','M','J','J','A','S','O','N','D'),
position = "bottom") +
labs(x = "", y = "No. of estimates in N/S Hemisphere")Combine plots
ggarrange(OceanMapM, Hemi, widths = c(3,1), labels = c("A","B"))
## {-}
Figure 2
Changes in disease prevalence over the three factors: average summer sea surface temperature (SST) in °C, weekly sea surface temperature anomaly (WSSTA) in °C-weeks, and Year
# Colour palette
palette()
# getting data from the model
dat <- no_interaction$dataFigure 2A
# summer temp
# plotting lines
means_fixed <- no_interaction %>%
emmeans(~ sSumTemp,
at = list(sSumTemp = seq(min(dat$sSumTemp),max(dat$sSumTemp),length.out = 100)),
epred = TRUE,
re_formula = NA) %>% as_tibble() %>%
mutate(rSumTemp = (sSumTemp*meanSD$SumTemp_SD + meanSD$SumTemp_mean))
#adding rSumTemp to dat
dat <- dat %>%
mutate(rSumTemp = (sSumTemp*meanSD$SumTemp_SD + meanSD$SumTemp_mean))
# putting bubbles in plot
temp1 <- ggplot()+
# confidence interval
geom_smooth(data = means_fixed, aes(x = rSumTemp, y = lower.HPD), method = "loess", formula = y~x, se = FALSE, lty = "dotted", lwd = 0.5, col = "black") +
geom_smooth(data = means_fixed, aes(x = rSumTemp, y = upper.HPD), method = "loess", formula = y~x, se = FALSE, lty = "dotted", lwd = 0.5, col = "black") +
# main line
geom_smooth(data = means_fixed, aes(x = rSumTemp, y = emmean), method = "loess", formula = y~x, se = FALSE, lwd = 1, col = "black") +
geom_point(data = dat, aes(x = rSumTemp, y = Disease_P, size = logArea, fill = Ocean), shape = 21, alpha = 0.5) +
scale_fill_viridis_d(end = 0.9) +
scale_colour_viridis_d(end = 0.9) +
#facet_grid(rows = vars(condition)) +
labs(y = "Proportion of disease prevalence", x = "Average Summer SST (\u00B0C)", size = expression(paste("log(Area Examined [", cm^2, "])", sep = "")), fill = "Ocean") +
ylim(0, 1.0) + xlim(24.5, 32.5) +
# themes
theme_bw(base_size = 12) + theme(legend.position="bottom", legend.box="vertical", legend.margin=margin())Figure 2B
# plotting gradients
means_draws <- no_interaction %>%
emmeans(~ sSumTemp,
at = list(sSumTemp = seq(min(dat$sSumTemp),max(dat$sSumTemp),length.out = 100)),
epred = TRUE,
re_formula = NA) %>%
gather_emmeans_draws() %>%
mutate(rSumTemp = (sSumTemp*meanSD$SumTemp_SD + meanSD$SumTemp_mean))
temp2 <- ggplot(means_draws, aes(x = rSumTemp, y = .value)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Greys") +
labs(x = "Average Summer SST (\u00B0C)", y = "Proportion of disease prevalence",
fill = "Credible interval") +
ylim(0, 0.25) + xlim(24.5, 32.5) +
theme_bw(base_size = 12) +
theme(legend.position = "bottom")Figure 2C
# comparing min and max point
trends_draws <- no_interaction %>%
emtrends(~ sSumTemp, var = "sSumTemp",
at = list(sSumTemp = c((25-meanSD$SumTemp_mean)/meanSD$SumTemp_SD, (32-meanSD$SumTemp_mean)/meanSD$SumTemp_SD)), # 25 and 32 degree
regrid = "response") %>%
gather_emmeans_draws() %>%
mutate(rSumTemp = (sSumTemp*meanSD$SumTemp_SD + meanSD$SumTemp_mean))
# plot
temp3 <- ggplot(trends_draws, aes(x = .value, fill = factor(rSumTemp))) +
geom_vline(xintercept = 0) +
stat_halfeye(.width = c(0.8, 0.95), point_interval = "median_hdi",
slab_alpha = 0.75) +
scale_fill_viridis_d(option = "magma", begin = 0.4, end = 0.8) +
labs(x = "Average marginal effects at the two temperatures below",
y = "Density", fill = "rSumTemp",
caption = "80% and 95% credible intervals shown in black") +
theme_bw(base_size = 12) +
theme(legend.position = "bottom") +
labs(fill = "Average Summer SST (\u00B0C)")Figure 2D
# WSSTA
# plotting lines
means_fixed <- no_interaction %>%
emmeans(~ sWSSTA,
at = list(sWSSTA = seq(min(dat$sWSSTA),max(dat$sWSSTA),length.out = 100)),
epred = TRUE,
re_formula = NA) %>% as_tibble() %>%
mutate(rWSSTA = (sWSSTA*meanSD$WSSTA_SD + meanSD$WSSTA_mean))
#adding rWSSTA to dat
dat <- dat %>%
mutate(rWSSTA = (sWSSTA*meanSD$WSSTA_SD + meanSD$WSSTA_mean))
wssta1 <- ggplot()+
# confidence interval
geom_smooth(data = means_fixed, aes(x = rWSSTA, y = lower.HPD), method = "loess", formula = y~x, se = FALSE, lty = "dotted", lwd = 0.5, col = "black") +
geom_smooth(data = means_fixed, aes(x = rWSSTA, y = upper.HPD), method = "loess", formula = y~x, se = FALSE, lty = "dotted", lwd = 0.5, col = "black") +
# main line
geom_smooth(data = means_fixed, aes(x = rWSSTA, y = emmean), method = "loess", formula = y~x, se = FALSE, lwd = 1, col = "black") +
geom_point(data = dat, aes(x = rWSSTA, y = Disease_P, size = logArea, fill = Ocean), shape = 21, alpha = 0.5) +
scale_fill_viridis_d(end = 0.9) +
scale_colour_viridis_d(end = 0.9) +
labs(y = "Proportion of disease prevalence", x = "WSSTA (\u00B0C-weeks)",
fill = "Ocean",
size = expression(paste("log(Area Examined[", cm^2, "])", sep = ""))) +
ylim(0, 1.0) + xlim(0, 3.5) +
theme_bw(base_size = 12) + theme(legend.position="bottom", legend.box="vertical", legend.margin=margin()) +
guides(size = guide_legend(order = 1), fill = guide_legend(order = 2))Figure 2E
# plotting gradients
means_draws <- no_interaction %>%
emmeans(~ sWSSTA,
at = list(sWSSTA = seq(min(dat$sWSSTA),max(dat$sWSSTA),length.out = 100)),
epred = TRUE,
re_formula = NA) %>%
gather_emmeans_draws() %>%
mutate(rWSSTA = (sWSSTA*meanSD$WSSTA_SD + meanSD$WSSTA_mean))
wssta2 <- ggplot(means_draws, aes(x = rWSSTA, y = .value)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Greys") +
labs(x = "WSSTA (\u00B0C-weeks)", y = "Proportion of disease prevalence",
fill = "Credible interval") +
ylim(0, 0.25) + xlim(0, 3.5) +
theme_bw(base_size = 12) +
theme(legend.position = "bottom")Figure 2F
# comparing min and max point
trends_draws <- no_interaction %>%
emtrends(~ sWSSTA, var = "sWSSTA",
at = list(sWSSTA = c((0.4-meanSD$WSSTA_mean)/meanSD$WSSTA_SD, (4.3-meanSD$WSSTA_mean)/meanSD$WSSTA_SD)),
regrid = "response") %>%
gather_emmeans_draws() %>%
mutate(rWSSTA = (sWSSTA*meanSD$WSSTA_SD + meanSD$WSSTA_mean))
wssta3 <- ggplot(trends_draws, aes(x = .value, fill = factor(rWSSTA))) +
geom_vline(xintercept = 0) +
stat_halfeye(.width = c(0.8, 0.95), point_interval = "median_hdi",
slab_alpha = 0.75) +
scale_fill_viridis_d(option = "magma", begin = 0.4, end = 0.8) +
labs(x = "Average marginal effect at the two WSSTA values below",
y = "Density", fill = "rWSSTA",
caption = "80% and 95% credible intervals shown in black") +
theme_bw(base_size = 12) +
theme(legend.position = "bottom") +
labs(fill = "WSSTA (\u00B0C-weeks)")Figure 2G
# year
# plotting lines
means_fixed <- no_interaction %>%
emmeans(~ sYear,
at = list(sYear = seq(min(dat$sYear),max(dat$sYear),length.out = 100)),
epred = TRUE,
re_formula = NA) %>% as_tibble() %>%
mutate(rYear = (sYear*meanSD$Year_SD + meanSD$Year_mean))
#adding rYear to dat
dat <- dat %>%
mutate(rYear = (sYear*meanSD$Year_SD + meanSD$Year_mean))
# putting bubbles
year1 <- ggplot()+
# confidence interval
geom_smooth(data = means_fixed, aes(x = rYear, y = lower.HPD), method = "loess", formula = y~x, se = FALSE, lty = "dotted", lwd = 0.5, col = "black") +
geom_smooth(data = means_fixed, aes(x = rYear, y = upper.HPD), method = "loess", formula = y~x, se = FALSE, lty = "dotted", lwd = 0.5, col = "black") +
# main line
geom_smooth(data = means_fixed, aes(x = rYear, y = emmean), method = "loess", formula = y~x, se = FALSE, lwd = 1, col = "black") +
geom_point(data = dat, aes(x = rYear, y = Disease_P, size = logArea, fill = Ocean), shape = 21, alpha = 0.5) +
scale_fill_viridis_d(end = 0.9) +
scale_colour_viridis_d(end = 0.9) +
#facet_grid(rows = vars(condition)) +
labs(y = "Proportion of disease prevalence", x = "Year",
fill = "Ocean",
size = expression(paste("log(Area Examined [", cm^2, "])", sep = ""))) +
ylim(0, 1.0) + xlim(1990, 2020) +
# themes
theme_bw(base_size = 12) + theme(legend.position="bottom", legend.box="vertical", legend.margin=margin())Figure 2H
# plotting gradients
means_draws <- no_interaction %>%
emmeans(~ sYear,
at = list(sYear = seq(min(dat$sYear),max(dat$sYear),length.out = 100)),
epred = TRUE,
re_formula = NA) %>%
gather_emmeans_draws() %>%
mutate(rYear = (sYear*meanSD$Year_SD + meanSD$Year_mean))
year2 <- ggplot(means_draws, aes(x = rYear, y = .value)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Greys") +
labs(x = "Year", y = "Proportion of disease prevalence",
fill = "Credible interval") +
ylim(0, 0.25) + xlim(1990, 2020) +
theme_bw(base_size = 12) +
theme(legend.position = "bottom")Figure 2I
# comparing min and max point
trends_draws <- no_interaction %>%
emtrends(~ sYear, var = "sYear",
at = list(sYear = c((1992-meanSD$Year_mean)/meanSD$Year_SD, (2018-meanSD$Year_mean)/meanSD$Year_SD)),
regrid = "response") %>%
gather_emmeans_draws() %>%
mutate(rYear = (sYear*meanSD$Year_SD + meanSD$Year_mean))
year3 <- ggplot(trends_draws, aes(x = .value, fill = factor(rYear)), ) +
geom_vline(xintercept = 0) +
stat_halfeye(.width = c(0.8, 0.95), point_interval = "median_hdi",
slab_alpha = 0.75) +
scale_fill_viridis_d(option = "magma", begin = 0.4, end = 0.8) +
labs(x = "Average marginal effects at the two years below",
y = "Density", fill = "rYear",
caption = "80% and 95% credible intervals shown in black") +
theme_bw(base_size = 12) +
theme(legend.position = "bottom") +
labs(fill = "Year")Combine plots
(temp1 + temp2 + temp3) /
(wssta1 + wssta2 + wssta3) /
(year1 + year2 + year3) + plot_annotation(tag_levels = 'A') & theme(text = element_text(size = 12))
## {-}
Figure 3
Global disease prevalence prediction depicted three ways
Figure 3A
# summer temp
# new data range
sSumTemp_seq <- seq(min(dat$sSumTemp),max(dat$sSumTemp),length.out = 100)
# creating new data
new_st<- expand_grid(
sYear = 0,
sSumTemp = sSumTemp_seq,
sWSSTA = 0,
sDisease_Num = 0,
Ocean = c("Atlantic Ocean","Pacific Ocean","Indian Ocean") # this is for Atlantic
)
res_draws <- no_interaction %>%
epred_draws(newdata = new_st, dpar = c("mu", "zi", "phi"), re_formula = NA) %>%
group_by(sSumTemp, .draw) %>% summarise(sSumTemp = mean(sSumTemp),
rSumTemp = (sSumTemp*meanSD$SumTemp_SD + meanSD$SumTemp_mean),
predicted = mean(.epred),
mu = mean(mu),
zi = mean(zi),
phi = mean(phi))
# mu
temp_mu <- ggplot(res_draws, aes(x = rSumTemp, y = mu)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Reds") +
labs(x = "Average Summer SST (\u00B0C)", y = "Proportion of disease prevalence",
fill = "Credible interval") +
theme_bw(base_size = 12) +
theme(legend.position = "none")Figure 3B
# zi
temp_zi <- ggplot(res_draws, aes(x = rSumTemp, y = zi)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Blues") +
labs(x = "Average Summer SST (\u00B0C)", y = "Proportion of 0 disease prevalence",
fill = "Credible interval") +
theme_bw(base_size = 12) +
theme(legend.position = "none")Figure 3C
# phi
temp_phi <- ggplot(res_draws, aes(x = rSumTemp, y = phi)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Greens") +
labs(x = "Average Summer SST (\u00B0C)", y = "Precison (1/SE) of disease prevalence",
fill = "Credible interval") +
theme_bw(base_size = 12) +
theme(legend.position = "none")Figure 3D
# WSSTA
# new data range
sWSSTA_seq <- seq(min(dat$sWSSTA),max(dat$sWSSTA),length.out = 100)
# creating new data
new_wssta<- expand_grid(
sYear = 0,
sSumTemp = 0,
sWSSTA = sWSSTA_seq,
sDisease_Num = 0,
Ocean = c("Atlantic Ocean","Pacific Ocean","Indian Ocean") # this is for Atlantic
)
res_draws <- no_interaction %>%
epred_draws(newdata = new_wssta, dpar = c("mu", "zi", "phi"), re_formula = NA) %>%
group_by(sWSSTA, .draw) %>% summarise(sWSSTA = mean(sWSSTA),
rWSSTA = (sWSSTA*meanSD$WSSTA_SD + meanSD$WSSTA_mean),
predicted = mean(.epred),
mu = mean(mu),
zi = mean(zi),
phi = mean(phi))
# mu
wssta_mu <- ggplot(res_draws, aes(x = rWSSTA, y = mu)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Reds") +
labs(x = "WSSTA (\u00B0C-weeks)", y = "Proportion of disease prevalence",
fill = "Credible interval") +
#ylim(0, 0.30) +
xlim(0, 3.5) +
theme_bw(base_size = 12) +
theme(legend.position = "none")
#theme(legend.position = "bottom")Figure 3E
# zi
wssta_zi <- ggplot(res_draws, aes(x = rWSSTA, y = zi)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Blues") +
labs(x = "WSSTA (\u00B0C-weeks)", y = "Proportion of 0 disease prevalence",
fill = "Credible interval") +
#ylim(0, 0.30) +
xlim(0, 3.5) +
theme_bw(base_size = 12) +
theme(legend.position = "none")
#theme(legend.position = "bottom")Figure 3F
# phi
wssta_phi <- ggplot(res_draws, aes(x = rWSSTA, y = phi)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Greens") +
labs(x = "WSSTA (\u00B0C-weeks)", y = "Precison (1/SE) of disease prevalence",
fill = "Credible interval") +
xlim(0, 3.5) +
theme_bw(base_size = 12) +
theme(legend.position = "none")Figure 3G
# year
# new data range
sYear_seq <- seq(min(dat$sYear),max(dat$sYear),length.out = 100)
# creating new data
new_year<- expand_grid(
sYear = sYear_seq,
sSumTemp = 0,
sWSSTA = 0,
sDisease_Num = 0,
Ocean = c("Atlantic Ocean","Pacific Ocean","Indian Ocean") # this is for Atlantic
)
res_draws <- no_interaction %>%
epred_draws(newdata = new_year, dpar = c("mu", "zi", "phi"), re_formula = NA) %>%
group_by(sYear, .draw) %>% summarise(sYear = mean(sYear),
rYear = (sYear*meanSD$Year_SD + meanSD$Year_mean),
predicted = mean(.epred),
mu = mean(mu),
zi = mean(zi),
phi = mean(phi))
# mu
year_mu <- ggplot(res_draws, aes(x = rYear, y = mu)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Reds") +
labs(x = "Year", y = "Proportion of disease prevalence",
fill = "Credible interval for mu") +
theme_bw(base_size = 12) +
theme(legend.position = "bottom")Figure 3H
# zi
year_zi <- ggplot(res_draws, aes(x = rYear, y = zi)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Blues") +
labs(x = "Year", y = "Proportion of 0 disease prevalence",
fill = "Credible interval for zi") +
theme_bw(base_size = 12) +
theme(legend.position = "bottom")Figure 3I
# phi
year_phi <- ggplot(res_draws, aes(x = rYear, y = phi)) +
stat_lineribbon() +
scale_fill_brewer(palette = "Greens") +
labs(x = "Year", y = "Precison (1/SE) of disease prevalence",
fill = "Credible interval for phi") +
theme_bw(base_size = 12) +
theme(legend.position = "bottom")Combine plots
(temp_mu + temp_zi + temp_phi) /
(wssta_mu + wssta_zi + wssta_phi) /
(year_mu + year_zi + year_phi) + plot_annotation(tag_levels = 'A') & theme(text = element_text(size = 12))
## {-}
Figure 4
Three oceans’ predicted non-zero values (mu) of disease prevalence per fixed variable
Getting data ready
dat <-YearxOcean_SSTxOcean$dataFigure 4A
# summer temp
# create new data
means_fixed <- YearxOcean_SSTxOcean %>%
emmeans(~ sSumTemp + Ocean,
at = list(sSumTemp = seq(min(dat$sSumTemp),max(dat$sSumTemp),length.out = 100)),
epred = TRUE,
re_formula = NA) %>%
gather_emmeans_draws() %>%
mutate(rSumTemp = (sSumTemp*meanSD$SumTemp_SD + meanSD$SumTemp_mean))
# separate data by ocean and plot
means_fixed_A <- subset(means_fixed, Ocean == "Atlantic Ocean")
means_fixed_I <- subset(means_fixed, Ocean == "Indian Ocean")
means_fixed_P <- subset(means_fixed, Ocean == "Pacific Ocean")
# Atlantic Ocean
temp_A <- ggplot(means_fixed_A, aes(x = rSumTemp, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d() +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
#facet_wrap(vars(Ocean), ncol = 3) +
labs(x = "Average Summer SST (\u00B0C)",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.35) +
theme(legend.position = "none", text = element_text(size = 12))Figure 4B
# Indian Ocean
temp_I <- ggplot(means_fixed_I, aes(x = rSumTemp, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d(begin = 0.45) +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "Average Summer SST (\u00B0C)",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.35) +
theme(legend.position = "none", text = element_text(size = 12))Figure 4C
# Pacific Ocean
temp_P <- ggplot(means_fixed_P, aes(x = rSumTemp, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d(begin = 0.9) +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "Average Summer SST (\u00B0C)",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.35) +
theme(legend.position = "none", text = element_text(size = 12))Figure 4D
#wssta
# create new data
means_fixed <- YearxOcean_SSTxOcean %>%
emmeans(~ sWSSTA + Ocean,
at = list(sWSSTA = seq(min(dat$sWSSTA),max(dat$sWSSTA),length.out = 100)),
epred = TRUE,
re_formula = NA) %>%
gather_emmeans_draws() %>%
mutate(rWSSTA = (sWSSTA*meanSD$WSSTA_SD + meanSD$WSSTA_mean))
# separate data by ocean and plot
means_fixed_A <- subset(means_fixed, Ocean == "Atlantic Ocean")
means_fixed_I <- subset(means_fixed, Ocean == "Indian Ocean")
means_fixed_P <- subset(means_fixed, Ocean == "Pacific Ocean")
# Atlantic Ocean
wssta_A <- ggplot(means_fixed_A, aes(x = rWSSTA, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d() +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "WSSTA (\u00B0C-weeks)",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.2) +
xlim(0,3.5) +
theme(legend.position = "none", text = element_text(size = 12))Figure 4E
# Indian Ocean
wssta_I <- ggplot(means_fixed_I, aes(x = rWSSTA, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d(begin = 0.45) +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "WSSTA (\u00B0C-weeks)",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.2) +
xlim(0,3.5) +
theme(legend.position = "none", text = element_text(size = 12))Figure 4F
# Pacific Ocean
wssta_P <- ggplot(means_fixed_P, aes(x = rWSSTA, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d(begin = 0.9) +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "WSSTA (\u00B0C-weeks)",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.2) +
xlim(0,3.5) +
theme(legend.position = "none", text = element_text(size = 12))Figure 4G
# year
# create new data
means_fixed <- YearxOcean_SSTxOcean %>%
emmeans(~ sYear + Ocean,
at = list(sYear = seq(min(dat$sYear),max(dat$sYear),length.out = 100)),
epred = TRUE,
re_formula = NA) %>%
gather_emmeans_draws() %>%
mutate(rYear = (sYear*meanSD$Year_SD + meanSD$Year_mean))
# separate data by ocean and plot
means_fixed_A <- subset(means_fixed, Ocean == "Atlantic Ocean")
means_fixed_I <- subset(means_fixed, Ocean == "Indian Ocean")
means_fixed_P <- subset(means_fixed, Ocean == "Pacific Ocean")
# Atlantic Ocean
year_A <- ggplot(means_fixed_A,
aes(x = rYear, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d() +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "Year",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.35) +
theme(legend.position = "bottom", text = element_text(size = 12))Figure 4H
# Indian Ocean
year_I <- ggplot(means_fixed_I,
aes(x = rYear, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d(begin = 0.45) +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "Year",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.35) +
theme(legend.position = "bottom", text = element_text(size = 12))Figure 4I
# Pacific Ocean
year_P <- ggplot(means_fixed_P,
aes(x = rYear, y = (.value), color = Ocean, fill = Ocean)) +
stat_lineribbon(aes(fill_ramp = stat(level))) +
scale_fill_viridis_d(begin = 0.9) +
scale_colour_viridis_d(option = "B", end = 0) +
scale_fill_ramp_discrete(range = c(0.2, 0.7)) +
labs(x = "Year",
y = "Proportion of disease prevalence",
fill_ramp = "Credible interval") +
theme_bw(base_size = 14) +
ylim(0, 0.35) +
theme(legend.position = "bottom", text = element_text(size = 12))Combine plots
(temp_A + temp_I + temp_P) /
(wssta_A + wssta_I + wssta_P) /
(year_A + year_I + year_P) + plot_annotation(tag_levels = 'A') +
plot_layout(guides = "collect") &
theme(legend.position='bottom',
text = element_text(size = 12))
## {-}
Figure S4
Correlation between Average Summer SST and Year
ggplot(rdsdat) +
geom_point(aes(y = average_SST_summer, x = Year)) +
labs(y = "Average Summer SST (\u00B0C)") +
theme_bw()Figure S5
Visual description of WSSTA calculation
# define an updated comparison operator that will work well with values differing beyond the floating point precision limit
`%===%` <- function(x, y, tol = 1e-7) {
if(length(x) == 1) {
a = x; b = y
} else {
a = y; b = x
}
if(length(a) == 1 & length(b) == 1) {
testout <- isTRUE(all.equal(x, y, tolerance = tol))
}
if(length(a) == 1 | length(b) == 1) {
testout <- sapply(b, function(n, num) isTRUE(all.equal(n, num, tolerance = tol)), num = a)
}
if(length(a) > 1 & length(b) > 1) {
testout <- mapply(function(n, m) isTRUE(all.equal(n, m, tolerance = tol)), a, b)
if(length(a) != length(b)) warning("Objects differ in length, recycling the shorter object!")
}
return(testout)
}
# tests of the function
1 %===% 1
c(1,2,3) %===% 2
c(1,2,3) %===% c(3,2,4)
2 %===% c(3,2,4)
2.0005 %===% c(3,2,4)
2.00000006 %===% c(3,2.00000003,4)
2 %===% c(3,2.00000003,4)
c(1,2,3,4) %===% c(1,3)
# open a connection to a sample file to see its attributes
# (commented as it's usable only with all individual files available)
# nc_temp <- nc_open('./2015/20150101120000-ESACCI-L4_GHRSST-SSTdepth-OSTIA-GLOB_CDR2.1-v02.0-fv01.0.nc')
# print(nc_temp)
# example of extracting only some of a specific variable
# varpart <- ncvar_get(nc_temp, "analysed_sst", start = c(1,50,1), count = c(-1,10,1))
# is equivalent to this
# varpart <- ncvar_get(nc_temp, "analysed_sst", start = c(1,50), count = c(-1,10))
# dimensions are provided as X-Y-(Z)-T, and they are lon-lat-time
# extract the allowed values of dimensions
# (commented for reasons explained above)
# lonvar <- ncvar_get(nc_temp, "lon")
# latvar <- ncvar_get(nc_temp, "lat")
# reload limited data (defined largely in several commented lines)
# note: full NC file data are not included in repo due to their size
load(here('R', 'dhw_illustration_plot', 'required.Rdata'))
# load climatology
mmm <- nc_open(here("data",'ct5km_climatology_v3.1.nc'))
lons <- round(ncvar_get(mmm, 'lon'), 3)
lats <- round(ncvar_get(mmm, 'lat'), 3)
# check coordinates
lon_index <- which(lonvar %===% round(floor(114.6548/0.05)*0.05 + 0.025, 3))
lat_index <- which(latvar %===% round(floor(-8.14028/0.05)*0.05 + 0.025, 3))
mmmlon <- which(lons %===% round(floor(lonvar[lon_index]/0.05)*0.05 + 0.025, 3))
mmmlat <- which(lats %===% round(floor(latvar[lat_index]/0.05)*0.05 + 0.025, 3))
# (commented for reasons explained above)
# sst_ts <- c()
# for(i in list.files("./2017/")) {
# nc_temp <- nc_open(paste0("./2017/", i))
# sst_data <- ncvar_get(nc_temp, "analysed_sst",
# start = c(lon_index, lat_index, 1), count = c(1,1,1))
# sst_ts <- c(sst_ts, sst_data)
# nc_close(nc_temp)
# }
# repeat above code to load separate sst data for 2015, 2016, 2017
# sst_ts -> sst_ts_2015
# sst_ts -> sst_ts_2016
# sst_ts -> sst_ts_2017
# below code saves .Rdata file that is later used to reload yearly data
# limited to specific coordinates
# save(list = c('sst_ts_2015', 'sst_ts_2016', 'sst_ts_2017', 'lonvar', 'latvar'),
# file = here('R', 'dhw_illustration_plot', 'required.Rdata'))
# extract location's climatology
mmm_climatology <- c(
ncvar_get(mmm, "sst_clim_january", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_february", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_march", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_april", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_may", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_june", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_july", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_august", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_september", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_october", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_november", start = c(mmmlon, mmmlat, 1), count = c(1,1,1)),
ncvar_get(mmm, "sst_clim_december", start = c(mmmlon, mmmlat, 1), count = c(1,1,1))
)
mmm_climatology
sst_ts <- sst_ts_2017 # change this to change year (data are: sst_ts_2015/2016/2017)
data <- data.frame(day = 1:length(sst_ts), sst = sst_ts-273)
# calculate month middles (floor-rounded)
# define months
months <- c(31,29,31,30,31,30,31,31,30,31,30,31)
months_cumul <- c(1, cumsum(months))
m_mids <- c()
for (i in 1:12) {
mid <- floor((months_cumul[i] + months_cumul[i+1])/2)
m_mids <- c(m_mids, mid)
}
weeks <- c(1, 1:52 * 7)
w_mids <- c()
for (i in 1:length(weeks)) {
mid <- floor((weeks[i] + weeks[i+1])/2)
if(!is.na(mid)) w_mids <- c(w_mids, mid)
}
i <- 1
sst_weekly <- c()
for(temp in data$sst) {
if(i == 1) sst_avg <- temp*1/7
else sst_avg <- sst_avg + temp*1/7
if(i == 7) {sst_weekly <- c(sst_weekly, sst_avg); i <- 1}
else i <- i+1
}
data.w <- data.frame(w_mids = w_mids, w_means = sst_weekly,
wssta = cumsum(ifelse(sst_weekly > max(mmm_climatology)+1,
sst_weekly-max(mmm_climatology)+1, 0)))
# scale and fact are used to transform the second y axis
scale <- 25
fact <- 25
plot <- ggplot(data = data, mapping = aes(x = day)) +
geom_hline(yintercept = max(mmm_climatology), lty = 5, lwd = 0.5, col = 'purple') +
geom_hline(yintercept = max(mmm_climatology) + 1, lty = 5, lwd = 0.5, col = 'red') +
scale_x_continuous(breaks = months_cumul) +
scale_y_continuous(name = 'Sea Surface Temperature (\u00B0C)', limits = c(25, 31),
sec.axis = sec_axis(~(.-fact)*scale, name = "Cumulative Heat Stress (\u00B0C-weeks)")) +
geom_line(aes(y = sst), col = 'gray80', lwd = 1.5) +
geom_segment(data = subset(data.w, w_means > max(mmm_climatology) + 1),
aes(x = w_mids, y = max(mmm_climatology) + 1, xend = w_mids, yend = w_means),
lwd = 2, col = 'coral') +
geom_point(data = data.frame(m_mids = m_mids, m_means = mmm_climatology),
aes(x = m_mids, y = m_means), shape = 3, size = 5, col = 'red', stroke = 1) +
geom_point(data = data.w,
aes(x = w_mids, y = w_means), shape = 19, size = 2.5, col = 'gray40') +
geom_ribbon(data = data.w, aes(x = w_mids, ymax = (wssta/scale)+fact), ymin = fact, fill = 'red', alpha = 0.1) +
geom_line(data = data.w, aes(x = w_mids, y = (wssta/scale)+fact), col = 'coral', lwd = 3) +
geom_point(x = max(data.w$w_mids), y = max((data.w$wssta/scale)+fact), shape = 19, size = 6, col = 'coral') +
theme_bw() +
theme(panel.grid.minor.x = element_blank(), text = element_text(size = 20)) +
labs(x = 'Days')
plotFigure S7
Phylogenetic Tree of included species
genus <- unique(prevSPP$Genus[prevSPP$Genus != "Helioseris"]) # Removed the Genus Helioseris because it was removed from the analysed dataset because of the disease prevalence metric used
taxa_list <- na.omit(genus)
taxa_list2 <- as.factor(taxa_list)
taxa <- tnrs_match_names(names = levels(taxa_list2), context_name = "Animals") # Connect the list of Genera with the Open Tree taxonomy
taxa.in.tree <- ott_id(taxa)[is_in_tree(ott_id(taxa))]
tree <- tol_induced_subtree(ott_ids = taxa.in.tree, label_format = "name")tree$tip.label <- gsub("_\\(.*","", tree$tip.label) # Remove symbols
plain_tree <- plot(tree, cex = 0.5, label.offset = 0.1, no.margin = TRUE) is.binary(tree) # Check if binary## [1] FALSE
tree <- compute.brlen(tree, method = "Grafen", power = 1) # Compute branch lengths
all_taxa <- intersect(as.character(tree$tip.label), taxa_list) # Find synonyms and typos and remove them
used_taxa <- setdiff(as.character(tree$tip.label), taxa_list)
# Build heatmap of oceans
species <- select(prevSPP, "PaperID", "Genus")
species$Paper_ID <- species$PaperID
dat.tree <- left_join(rdsdat, species, by = c("Paper_ID")) # Join the data with the Genus information
dat.tree <- select(dat.tree, Paper_ID, Genus, Ocean) # Reduce the data to the needed columns
dat.tree <- mutate(dat.tree, search_string = decapitalize(Genus)) # Decapitalize "Genus" to match the "search string" in the "taxa" file
dat.tree <- left_join(dat.tree, select(taxa, search_string, unique_name, ott_id), by = "search_string") # Join taxa information from rotl to the dataset
dat.tree$unique_name <- word(dat.tree$unique_name, 1) # Only keep one word for the Genus (we had e.g. "Stylophora (genus in phylum Cnidaria)")
dat.tree <- dat.tree[dat.tree$unique_name %in% tree$tip.label, ] # Check that the Genera match the ones used in the tree
ocean <- dat.tree %>% group_by(unique_name) %>% summarise(
oceanIndian = Ocean == "Indian Ocean",
oceanAtlantic = Ocean == "Atlantic Ocean",
oceanPacific = Ocean == "Pacific Ocean")
ocean <- distinct(ocean) # Only keep unique rows
ocean$oceanIndian = as.numeric(ocean$oceanIndian) # convert TRUE/FALSE to binary values for each Ocean
ocean$oceanAtlantic = as.numeric(ocean$oceanAtlantic)
ocean$oceanPacific = as.numeric(ocean$oceanPacific)
ocean <- ocean %>% group_by(unique_name) %>% summarise(oceanIndian=sum(oceanIndian), # calculate the sum for each species (i.e., if 1, the species is found in the designated ocean)
oceanAtlantic=sum(oceanAtlantic),
oceanPacific=sum(oceanPacific))
ocean$oceanIndian=as.factor(ocean$oceanIndian) # Convert back to factor for the plot
ocean$oceanAtlantic=as.factor(ocean$oceanAtlantic)
ocean$oceanPacific=as.factor(ocean$oceanPacific)
# Plot Horizontal Tree
# simple phylogenetic tree
htree <- ggtree(tree, lwd = 1.05) +
geom_tiplab(offset = 0.04) # Display Genus
h <- htree %<+% ocean # Link plot to data
# plot tree and heatmap together
h2 <- h + geom_fruit(geom=geom_tile,
mapping=aes(fill=oceanAtlantic),
width=0.075,
offset=0.35) +
scale_fill_manual(name = "", values=c("white", "#7C4F85"), labels=c("", "Atlantic Ocean"), guide = guide_legend(order = 1)) +
new_scale_fill() +
geom_fruit(geom=geom_tile,
mapping=aes(fill=oceanIndian),
width=0.075,
offset=0.075)+
scale_fill_manual(name = "", values=c("white","#71A8AF"), labels=c("", "Indian Ocean"), guide = guide_legend(order = 2))+
new_scale_fill() +
geom_fruit(geom=geom_tile,
mapping=aes(fill=oceanPacific),
width=0.075,
offset=0.075)+
scale_fill_manual(name = "", values=c("white", "#D4E974"), labels=c("", "Pacific Ocean"), guide = guide_legend(order = 3))
h2Figure S8
No interaction contrasts
Average Summer SST
# create new data
trends_draws2 <- no_interaction %>%
emtrends(~ sSumTemp, var = "sSumTemp",
at = list(sSumTemp = c((25-meanSD$SumTemp_mean)/meanSD$SumTemp_SD, (32-meanSD$SumTemp_mean)/meanSD$SumTemp_SD)), # 25 and 32 degree
regrid = "response") %>%
contrast(method = "revpairwise") %>%
gather_emmeans_draws()
# plot contrast
temp_cont <- ggplot(trends_draws2, aes(x = .value)) +
geom_vline(xintercept = 0, linetype = "dotted") +
stat_halfeye(.width = c(0.8, 0.95), point_interval = "median_hdi",
fill = "grey65") +
labs(x = "Difference in marginal effects between 25\u00B0C and 32\u00B0C", y = NULL) +
theme_bw() WSSTA
# create new data
trends_draws2 <- no_interaction %>%
emtrends(~ sWSSTA, var = "sWSSTA",
at = list(sWSSTA = c((0.4-meanSD$WSSTA_mean)/meanSD$WSSTA_SD, (4.3-meanSD$WSSTA_mean)/meanSD$WSSTA_SD)),
regrid = "response") %>%
contrast(method = "revpairwise") %>%
gather_emmeans_draws()
wssta_cont <- ggplot(trends_draws2, aes(x = .value)) +
stat_halfeye(.width = c(0.8, 0.95), point_interval = "median_hdi",
fill = "grey65") +
labs(x = "Difference in marginal effects between 0.4\u00B0C-weeks and 4.3\u00B0C-weeks", y = NULL) +
theme_bw() +
geom_vline(xintercept = 0, linetype = "dotted")Year
# create new data
trends_draws2 <- no_interaction %>%
emtrends(~ sYear, var = "sYear",
at = list(sYear = c((1992-meanSD$Year_mean)/meanSD$Year_SD, (2018-meanSD$Year_mean)/meanSD$Year_SD)),
regrid = "response") %>%
contrast(method = "revpairwise") %>%
gather_emmeans_draws()
# plot contrast
year_cont <- ggplot(trends_draws2, aes(x = .value)) +
stat_halfeye(.width = c(0.8, 0.95), point_interval = "median_hdi",
fill = "grey65") +
labs(x = "Difference in marginal effects between 1988 and 2018", y = NULL,
caption = "80% and 95% credible intervals shown in black") +
theme_bw() +
geom_vline(xintercept = 0, linetype = "dotted")Contrast figure
temp_cont + wssta_cont + year_cont + plot_annotation(tag_levels = 'A') & theme(text = element_text(size = 12))
## {-}
Figure S9
Ocean contrast plots
Average Summer SST
# create new data
trends_draws <- YearxOcean_SSTxOcean %>%
emtrends(~ Ocean, var = "sSumTemp",
#at = list(sSumTemp = c(0)),
regrid = "none") %>%
contrast(method = "pairwise") %>%
gather_emmeans_draws()
# plot contrast
cont_temp <- ggplot(trends_draws,
aes(x = .value, fill = factor(contrast))) +
stat_halfeye(slab_alpha = 0.75) +
scale_fill_okabe_ito(order = c(3, 4, 5)) +
facet_wrap(vars(contrast)) +
theme_bw() +
labs(x = "Difference in marginal effects between 25\u00B0C and 32\u00B0C", y = NULL) +
theme(legend.position = "none")WSSTA
No WSSTA since there was no interaction with Ocean
Year
# create new data
trends_draws <- YearxOcean_SSTxOcean %>%
emtrends(~ Ocean, var = "sYear",
#at = list(sSumTemp = c(0)),
regrid = "none") %>%
contrast(method = "pairwise") %>%
gather_emmeans_draws()
# plot contrast
cont_year<- ggplot(trends_draws,
aes(x = .value, fill = factor(contrast))) +
stat_halfeye(slab_alpha = 0.75) +
scale_fill_okabe_ito(order = c(3, 4, 5)) +
facet_wrap(vars(contrast)) +
theme_bw() +
labs(x = "Difference in marginal effects between 1992 and 2018", y = NULL,
caption = "80% and 95% credible intervals shown in black") +
theme(legend.position = "bottom", legend.title=element_blank())Contrast figure
cont_temp / cont_year + plot_annotation(tag_levels = 'A') & theme(text = element_text(size = 12))
## {-}
Software and Package Versions
sessionInfo()## R version 4.2.0 (2022-04-22 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22000)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_United States.utf8
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] kableExtra_1.3.4 ggExtra_0.10.0 ggpubr_0.4.0
## [4] igraph_1.3.1 ggdist_3.1.1 ggbeeswarm_0.6.0
## [7] gghalves_0.1.1 ggokabeito_0.1.0 patchwork_1.1.1
## [10] emmeans_1.7.3 broom.mixed_0.2.9.4 broom_0.8.0
## [13] tidybayes_3.0.2 brms_2.17.0 Rcpp_1.0.8.3
## [16] modelr_0.1.8 glmmTMB_1.1.3 rstan_2.21.5
## [19] StanHeaders_2.21.0-7 lme4_1.1-29 Matrix_1.4-1
## [22] birk_2.1.2 RCurl_1.98-1.6 lubridate_1.8.0
## [25] ncdf4_1.19 R.utils_2.11.0 R.oo_1.24.0
## [28] R.methodsS3_1.8.1 ggnewscale_0.4.7 ggtreeExtra_1.7.0
## [31] ggtree_3.5.0.901 BiocManager_1.30.17 RDS_0.9-3
## [34] ape_5.6-2 rotl_3.0.12 here_1.0.1
## [37] maps_3.4.0 visdat_0.5.3 readxl_1.4.0
## [40] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.8
## [43] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0
## [46] tibble_3.1.6 ggplot2_3.3.5 tidyverse_1.3.1
##
## loaded via a namespace (and not attached):
## [1] estimability_1.3 coda_0.19-4 knitr_1.39
## [4] dygraphs_1.1.1.6 data.table_1.14.2 rpart_4.1.16
## [7] inline_0.3.19 generics_0.1.2 cowplot_1.1.1
## [10] callr_3.7.0 future_1.25.0 tzdb_0.3.0
## [13] webshot_0.5.4 xml2_1.3.3 httpuv_1.6.5
## [16] assertthat_0.2.1 xfun_0.30 hms_1.1.1
## [19] jquerylib_0.1.4 bayesplot_1.9.0 evaluate_0.15
## [22] promises_1.2.0.1 DEoptimR_1.0-11 fansi_1.0.3
## [25] progress_1.2.2 dbplyr_2.1.1 DBI_1.1.2
## [28] htmlwidgets_1.5.4 tensorA_0.36.2 stats4_4.2.0
## [31] ellipsis_0.3.2 crosstalk_1.2.0 backports_1.4.1
## [34] bookdown_0.26 markdown_1.1 RcppParallel_5.1.5
## [37] vctrs_0.4.1 abind_1.4-5 cachem_1.0.6
## [40] withr_2.5.0 robustbase_0.95-0 checkmate_2.1.0
## [43] treeio_1.21.0 xts_0.12.1 prettyunits_1.1.1
## [46] svglite_2.1.0 cluster_2.1.3 lazyeval_0.2.2
## [49] crayon_1.5.1 labeling_0.4.2 pkgconfig_2.0.3
## [52] nlme_3.1-157 vipor_0.4.5 nnet_7.3-17
## [55] rlang_1.0.2 globals_0.14.0 lifecycle_1.0.1
## [58] miniUI_0.1.1.1 colourpicker_1.1.1 ergm_4.1.2
## [61] cellranger_1.1.0 distributional_0.3.0 rprojroot_2.0.3
## [64] matrixStats_0.62.0 aplot_0.1.6 loo_2.5.1
## [67] carData_3.0-5 boot_1.3-28 zoo_1.8-10
## [70] reprex_2.0.1 base64enc_0.1-3 beeswarm_0.4.0
## [73] ggridges_0.5.3 processx_3.5.3 viridisLite_0.4.0
## [76] png_0.1-7 bitops_1.0-7 rncl_0.8.6
## [79] parallelly_1.31.1 rstatix_0.7.0 jpeg_0.1-9
## [82] shinystan_2.6.0 gridGraphics_0.5-1 ggsignif_0.6.3
## [85] scales_1.2.0 memoise_2.0.1 magrittr_2.0.3
## [88] plyr_1.8.7 threejs_0.3.3 compiler_4.2.0
## [91] rstantools_2.2.0 RColorBrewer_1.1-3 cli_3.3.0
## [94] listenv_0.8.0 ps_1.7.0 TMB_1.8.1
## [97] Brobdingnag_1.2-7 htmlTable_2.4.0 Formula_1.2-4
## [100] mgcv_1.8-40 MASS_7.3-56 tidyselect_1.1.2
## [103] stringi_1.7.6 highr_0.9 yaml_2.3.5
## [106] svUnit_1.0.6 latticeExtra_0.6-29 bridgesampling_1.1-2
## [109] grid_4.2.0 sass_0.4.1 tools_4.2.0
## [112] parallel_4.2.0 rstudioapi_0.13 foreign_0.8-82
## [115] gridExtra_2.3 trust_0.1-8 posterior_1.2.1
## [118] rmdformats_1.0.3 farver_2.1.0 digest_0.6.29
## [121] shiny_1.7.1 car_3.0-13 later_1.3.0
## [124] httr_1.4.2 colorspace_2.0-3 rvest_1.0.2
## [127] XML_3.99-0.9 fs_1.5.2 splines_4.2.0
## [130] yulab.utils_0.0.4 tidytree_0.3.9 shinythemes_1.2.0
## [133] ggplotify_0.1.0 systemfonts_1.0.4 xtable_1.8-4
## [136] jsonlite_1.8.0 nloptr_2.0.0 lpSolveAPI_5.5.2.0-17.7
## [139] rle_0.9.2 ggfun_0.0.6 R6_2.5.1
## [142] Hmisc_4.7-0 pillar_1.7.0 htmltools_0.5.2
## [145] mime_0.12 glue_1.6.2 fastmap_1.1.0
## [148] minqa_1.2.4 DT_0.22 codetools_0.2-18
## [151] pkgbuild_1.3.1 mvtnorm_1.1-3 furrr_0.2.3
## [154] utf8_1.2.2 lattice_0.20-45 bslib_0.3.1
## [157] network_1.17.1 numDeriv_2016.8-1.1 arrayhelpers_1.1-0
## [160] curl_4.3.2 rentrez_1.2.3 HDInterval_0.2.2
## [163] gtools_3.9.2 shinyjs_2.1.0 survival_3.3-1
## [166] rmarkdown_2.14 statnet.common_4.5.0 munsell_0.5.0
## [169] haven_2.5.0 reshape2_1.4.4 gtable_0.3.0